Shows
Learning Bayesian Statistics#73 A Guide to Plotting Inferences & Uncertainties of Bayesian Models, with Jessica HullmanProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I’m guessing you already tried to communicate the results of a statistical model to non-stats people — it’s hard, right? I’ll be honest: sometimes, I even prefer to take notes during meetings than doing that… But shhh, that’s out secret.But all of this was before. Before I talked with Jessica Hullman. Jessica is the Ginny Rometty associate professor of computer science at Northwestern University.Her work revolves around how to design interfaces to help people draw...
2022-12-231h 00
Learning Bayesian Statistics#72 Why the Universe is so Deliciously Crazy, with Daniel WhitesonProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!What happens inside a black hole? Can we travel back in time? Why is the Universe even here? This is the type of chill questions that we’re all asking ourselves from time to time — you know, when we’re sitting on the beach.This is also the kind of questions Daniel Whiteson loves to talk about in his podcast, “Daniel and Jorge Explain the Universe”, co-hosted with Jorge Cham, the author of PhD comics. Honestly, it’s one of my favorite...
2022-12-031h 13Learning Bayesian Statistics#72 Why the Universe is so Deliciously Crazy, with Daniel WhitesonProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!What happens inside a black hole? Can we travel back in time? Why is the Universe even here? This is the type of chill questions that we’re all asking ourselves from time to time — you know, when we’re sitting on the beach.This is also the kind of questions Daniel Whiteson loves to talk about in his podcast, “Daniel and Jorge Explain the Universe”, co-hosted with Jorge Cham, the author of PhD comics. Honestly, it’s one of my favorite...
2022-12-031h 13
Learning Bayesian Statistics#71 Artificial Intelligence, Deepmind & Social Change, with Julien CornebiseProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!This episode will show you different sides of the tech world. The one where you research and apply algorithms, where you get super excited about image recognition and AI-generated art. And the one where you support social change actors — aka the “AI for Good” movement.My guest for this episode is, quite naturally, Julien Cornebise. Julien is an Honorary Associate Professor at UCL. He was an early researcher at DeepMind where he designed its early algorithms. He then worked as a Dire...
2022-11-141h 05Learning Bayesian Statistics#71 Artificial Intelligence, Deepmind & Social Change, with Julien CornebiseProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!This episode will show you different sides of the tech world. The one where you research and apply algorithms, where you get super excited about image recognition and AI-generated art. And the one where you support social change actors — aka the “AI for Good” movement.My guest for this episode is, quite naturally, Julien Cornebise. Julien is an Honorary Associate Professor at UCL. He was an early researcher at DeepMind where he designed its early algorithms. He then worked as a Dire...
2022-11-141h 05
Learning Bayesian Statistics#70 Teaching Bayes for Biology & Biological Engineering, with Justin BoisProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Back in 2016, when I started dedicating my evenings and weekends to learning how to code and do serious stats, I was a bit lost… Where do I start? Which language do I pick? Why are all those languages just named with one single letter??Then I found some stats classes by Justin Bois — and it was a tremendous help to get out of that wood (and yes, this was a pun). I really loved Justin’s teaching because he was making...
2022-10-221h 05Learning Bayesian Statistics#70 Teaching Bayes for Biology & Biological Engineering, with Justin BoisProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Back in 2016, when I started dedicating my evenings and weekends to learning how to code and do serious stats, I was a bit lost… Where do I start? Which language do I pick? Why are all those languages just named with one single letter??Then I found some stats classes by Justin Bois — and it was a tremendous help to get out of that wood (and yes, this was a pun). I really loved Justin’s teaching because he was making...
2022-10-221h 05
Learning Bayesian Statistics#69 Why, When & How to use Bayes Factors, with Jorge TendeiroProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!A great franchise comes with a great rivalry: Marvel has Iron Man and Captain America; physics has General Relativity and Quantum Physics; and Bayesian stats has Posterior Estimation and… Bayes Factors!A few months ago, I had the pleasure of hosting EJ Wagenmakers, to talk about these topics. This time, I’m talking with Jorge Tendeiro, who has a different perspective on Null Hypothesis Testing in the Bayesian framework, and its relationship with generative models and posterior estimation.But...
2022-10-0553 minLearning Bayesian Statistics#69 Why, When & How to use Bayes Factors, with Jorge TendeiroProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!A great franchise comes with a great rivalry: Marvel has Iron Man and Captain America; physics has General Relativity and Quantum Physics; and Bayesian stats has Posterior Estimation and… Bayes Factors!A few months ago, I had the pleasure of hosting EJ Wagenmakers, to talk about these topics. This time, I’m talking with Jorge Tendeiro, who has a different perspective on Null Hypothesis Testing in the Bayesian framework, and its relationship with generative models and posterior estimation.But...
2022-10-0553 min
Learning Bayesian Statistics#68 Probabilistic Machine Learning & Generative Models, with Kevin MurphyProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Hosting someone like Kevin Murphy on your podcast is… complicated. Not because Kevin himself is complicated (he’s delightful, don’t make me say what I didn’t say!), but because all the questions I had for him amounted to a 12-hour show.Sooooo, brace yourselves folks!No, I'm kidding. Of course I didn’t do that folks, Kevin has a life! This life started in Ireland, where he was born. He grew up in England and got his BA fro...
2022-09-141h 05Learning Bayesian Statistics#68 Probabilistic Machine Learning & Generative Models, with Kevin MurphyProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Hosting someone like Kevin Murphy on your podcast is… complicated. Not because Kevin himself is complicated (he’s delightful, don’t make me say what I didn’t say!), but because all the questions I had for him amounted to a 12-hour show.Sooooo, brace yourselves folks!No, I'm kidding. Of course I didn’t do that folks, Kevin has a life! This life started in Ireland, where he was born. He grew up in England and got his BA fro...
2022-09-141h 05
Learning Bayesian Statistics#67 Exoplanets, Cool Worlds & Life in the Universe, with David KippingProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Is there life in the Universe? It doesn’t get deeper than this, does it? And yet, why do we care about that? In the very small chance that there is other life in the Universe, we have even less chance to discover it, talk to it and meet it. So, why do we care?Well, it may surprise you but Bayesian statistics helps us think about these astronomical and — dare I say? — philosophical topics, as my guest, David Kipping, will b...
2022-08-311h 00Learning Bayesian Statistics#67 Exoplanets, Cool Worlds & Life in the Universe, with David KippingProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Is there life in the Universe? It doesn’t get deeper than this, does it? And yet, why do we care about that? In the very small chance that there is other life in the Universe, we have even less chance to discover it, talk to it and meet it. So, why do we care?Well, it may surprise you but Bayesian statistics helps us think about these astronomical and — dare I say? — philosophical topics, as my guest, David Kipping, will b...
2022-08-311h 00
Learning Bayesian Statistics#66 Uncertainty Visualization & Usable Stats, with Matthew KayProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I have to confess something: I love challenges. And when you’re a podcaster, what’s a better challenge than dedicating an episode to… visualization? Impossible you say? Well, challenge accepted!Thankfully, I got the help of a visualization Avenger for this episode — namely, Matthew Kay. Matt is an Assistant Professor jointly appointed in Computer Science and Communications Studies at Northwestern University, where he co-directs the Midwest Uncertainty Collective — I know, it’s a pretty cool name for a lab.He wor...
2022-08-171h 01Learning Bayesian Statistics#66 Uncertainty Visualization & Usable Stats, with Matthew KayProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I have to confess something: I love challenges. And when you’re a podcaster, what’s a better challenge than dedicating an episode to… visualization? Impossible you say? Well, challenge accepted!Thankfully, I got the help of a visualization Avenger for this episode — namely, Matthew Kay. Matt is an Assistant Professor jointly appointed in Computer Science and Communications Studies at Northwestern University, where he co-directs the Midwest Uncertainty Collective — I know, it’s a pretty cool name for a lab.He wor...
2022-08-171h 01
Learning Bayesian Statistics#65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo VieiraProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Folks, there are some new cool kids on the block. They are called PyMC, Aeppl, and Aesara, and it’s high time we give us a proper welcome!To do that, who better than one of the architects of the new PyMC 4.0 — Ricardo Vieira! In this episode, he’ll walk us through the inner workings of the newly released version of PyMC, telling us why the Aesara backend and the brand new RandomVariable operators constitute such strong foundations for your belove...
2022-08-031h 05Learning Bayesian Statistics#65 PyMC, Aeppl, & Aesara: the new cool kids on the block, with Ricardo VieiraProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Folks, there are some new cool kids on the block. They are called PyMC, Aeppl, and Aesara, and it’s high time we give us a proper welcome!To do that, who better than one of the architects of the new PyMC 4.0 — Ricardo Vieira! In this episode, he’ll walk us through the inner workings of the newly released version of PyMC, telling us why the Aesara backend and the brand new RandomVariable operators constitute such strong foundations for your belove...
2022-08-031h 05
Learning Bayesian Statistics#64 Modeling the Climate & Gravity Waves, with Laura MansfieldProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I’m sure you’ve already heard of gravitational waves, because my listeners are the coolest and smartest ever ;) But did you know about gravity waves? That’s right, waves in the sky due to gravity — sounds awesome, right?Well, I’m pretty sure that Laura Mansfield will confirm your prior. Currently a postdoc at Stanford University, Laura studies — guess what? — gravity waves and how they are represented in climate models. In particular, she uses Bayesian methods to estimate the uncertainty on...
2022-07-201h 07Learning Bayesian Statistics#64 Modeling the Climate & Gravity Waves, with Laura MansfieldProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I’m sure you’ve already heard of gravitational waves, because my listeners are the coolest and smartest ever ;) But did you know about gravity waves? That’s right, waves in the sky due to gravity — sounds awesome, right?Well, I’m pretty sure that Laura Mansfield will confirm your prior. Currently a postdoc at Stanford University, Laura studies — guess what? — gravity waves and how they are represented in climate models. In particular, she uses Bayesian methods to estimate the uncertainty on...
2022-07-201h 07
Learning Bayesian Statistics#63 Media Mix Models & Bayes for Marketing, with Luciano PazProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Inviting someone like Luciano Paz on a stats podcast is both a pleasure and a challenge — he does so many things brilliantly that you have too many questions to ask him…In this episode, I’ve chosen — not without difficulty — to focus on the applications of Bayesian stats in the marketing industry, especially Media Mix Models. Ok, I also asked Luciano about other topics — but you know me, I like to talk…Originally, Luciano studied physics. He then did a PhD and...
2022-06-281h 14Learning Bayesian Statistics#63 Media Mix Models & Bayes for Marketing, with Luciano PazProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Inviting someone like Luciano Paz on a stats podcast is both a pleasure and a challenge — he does so many things brilliantly that you have too many questions to ask him…In this episode, I’ve chosen — not without difficulty — to focus on the applications of Bayesian stats in the marketing industry, especially Media Mix Models. Ok, I also asked Luciano about other topics — but you know me, I like to talk…Originally, Luciano studied physics. He then did a PhD and...
2022-06-281h 14
Learning Bayesian Statistics#62 Bayesian Generative Modeling for Healthcare, with Maria SkoularidouProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!We talk a lot about generative modeling on this podcast — at least since episode 6, with Michael Betancourt! And an area where this way of modeling is particularly useful is healthcare, as Maria Skoularidou will tell us in this episode.Maria is a final year PhD student at the University of Cambridge. Her thesis is focused on probabilistic machine learning and, more precisely, towards using generative modeling in… you guessed it: healthcare!But her fields of interest are diverse: from...
2022-06-0857 minLearning Bayesian Statistics#62 Bayesian Generative Modeling for Healthcare, with Maria SkoularidouProudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!We talk a lot about generative modeling on this podcast — at least since episode 6, with Michael Betancourt! And an area where this way of modeling is particularly useful is healthcare, as Maria Skoularidou will tell us in this episode.Maria is a final year PhD student at the University of Cambridge. Her thesis is focused on probabilistic machine learning and, more precisely, towards using generative modeling in… you guessed it: healthcare!But her fields of interest are diverse: from...
2022-06-0857 min
Learning Bayesian Statistics#61 Why we still use non-Bayesian methods, with EJ WagenmakersThe big problems with classic hypothesis testing are well-known. And yet, a huge majority of statistical analyses are still conducted this way. Why is it? Why are things so hard to change? Can you even do (and should you do) hypothesis testing in the Bayesian framework?I guess if you wanted to name this episode in a very Marvelian way, it would be “Bayes factors against the p-values of madness” — but we won’t do that, it wouldn’t be appropriate, would it?Anyways, in this episode, I’ll talk about all these very light and consensu...
2022-05-191h 16Learning Bayesian Statistics#61 Why we still use non-Bayesian methods, with EJ WagenmakersThe big problems with classic hypothesis testing are well-known. And yet, a huge majority of statistical analyses are still conducted this way. Why is it? Why are things so hard to change? Can you even do (and should you do) hypothesis testing in the Bayesian framework?I guess if you wanted to name this episode in a very Marvelian way, it would be “Bayes factors against the p-values of madness” — but we won’t do that, it wouldn’t be appropriate, would it?Anyways, in this episode, I’ll talk about all these very light and consensu...
2022-05-191h 16
Learning Bayesian Statistics#60 Modeling Dialogues & Languages, with J.P. de RuiterWhy do we, humans, communicate? And how? And isn’t that a problem that to study communication we have to… communicate?Did you ever ask yourself that? Because J.P. de Ruiter did — and does everyday. But he’s got good reasons: JP is a cognitive scientist whose primary research focus is on the cognitive foundations of human communication. He aims to improve our understanding of how humans and artificial agents use language, gesture and other types of signals to effectively communicate with each other.Currently he has one of the two Bridge Professorship at Tufts Uni...
2022-04-301h 12Learning Bayesian Statistics#60 Modeling Dialogues & Languages, with J.P. de RuiterWhy do we, humans, communicate? And how? And isn’t that a problem that to study communication we have to… communicate?Did you ever ask yourself that? Because J.P. de Ruiter did — and does everyday. But he’s got good reasons: JP is a cognitive scientist whose primary research focus is on the cognitive foundations of human communication. He aims to improve our understanding of how humans and artificial agents use language, gesture and other types of signals to effectively communicate with each other.Currently he has one of the two Bridge Professorship at Tufts Uni...
2022-04-301h 12
Learning Bayesian Statistics#59 Bayesian Modeling in Civil Engineering, with Michael FaberIn large-scale one-off civil infrastructure, decision-making under uncertainty is part of the job, that’s just how it is. But, civil engineers don't get the luxury of building 10^6 versions of the bridge, offshore wind turbine or aeronautical structure to consider a relative frequency interpretation!And as you’ll hear, challenges don’t stop there: you also have to consider natural hazards such as earthquakes, rockfall and typhoons — in case you were wondering, civil engineering is not among the boring jobs!To talk about these original topics, I had the pleasure to host Michael Faber. Michael is a Pro...
2022-04-1459 minLearning Bayesian Statistics#59 Bayesian Modeling in Civil Engineering, with Michael FaberIn large-scale one-off civil infrastructure, decision-making under uncertainty is part of the job, that’s just how it is. But, civil engineers don't get the luxury of building 10^6 versions of the bridge, offshore wind turbine or aeronautical structure to consider a relative frequency interpretation!And as you’ll hear, challenges don’t stop there: you also have to consider natural hazards such as earthquakes, rockfall and typhoons — in case you were wondering, civil engineering is not among the boring jobs!To talk about these original topics, I had the pleasure to host Michael Faber. Michael is a Pro...
2022-04-1459 min
Learning Bayesian Statistics#58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng LaoYou know when you have friends who wrote a book and pressure you to come on your podcast? That’s super annoying, right?Well that’s not what happened with Ravin Kumar, Osvaldo Martin and Junpeng Lao — I was the one who suggested doing a special episode about their new book, Bayesian Modeling and Computation in Python. And since they cannot say no to my soothing French accent, well, they didn’t say no…All of them were on the podcast already, so I’ll refer you to their solo episode for background on their background —...
2022-03-211h 09Learning Bayesian Statistics#58 Bayesian Modeling and Computation, with Osvaldo Martin, Ravin Kumar and Junpeng LaoYou know when you have friends who wrote a book and pressure you to come on your podcast? That’s super annoying, right?Well that’s not what happened with Ravin Kumar, Osvaldo Martin and Junpeng Lao — I was the one who suggested doing a special episode about their new book, Bayesian Modeling and Computation in Python. And since they cannot say no to my soothing French accent, well, they didn’t say no…All of them were on the podcast already, so I’ll refer you to their solo episode for background on their background —...
2022-03-211h 09
Learning Bayesian Statistics#57 Forecasting French Elections, with… Mystery GuestNo, no, don't leave! You did not click on the wrong button. You are indeed on Alex Andorra’s podcast. The podcast that took the Bayesian world by a storm: “Learning Bayesian Statistics”, and that Barack Obama deemed “the best podcast in the whole galaxy” – or maybe Alex said that, I don’t remember.Alex made us discover new methods, new ideas, and mostly new people. But what do we really know about him? Does he even really exist? To find this out I put on my Frenchest beret, a baguette under my arm, and went undercover to try to find...
2022-03-031h 21Learning Bayesian Statistics#57 Forecasting French Elections, with… Mystery GuestNo, no, don't leave! You did not click on the wrong button. You are indeed on Alex Andorra’s podcast. The podcast that took the Bayesian world by a storm: “Learning Bayesian Statistics”, and that Barack Obama deemed “the best podcast in the whole galaxy” – or maybe Alex said that, I don’t remember.Alex made us discover new methods, new ideas, and mostly new people. But what do we really know about him? Does he even really exist? To find this out I put on my Frenchest beret, a baguette under my arm, and went undercover to try to find...
2022-03-031h 21
Learning Bayesian Statistics#56 Causal & Probabilistic Machine Learning, with Robert Osazuwa NessDid you know there is a relationship between the size of firetrucks and the amount of damage down to a flat during a fire? The bigger the truck sent to put out the fire, the bigger the damages tend to be. The solution is simple: just send smaller firetrucks!Wait, that doesn’t sound right, does it? Our brain is a huge causal machine, so it can instinctively feel it’s not credible that size of truck and amount of damage done are causally related: there must be another variable explaining the correlation. Here, it’s of course...
2022-02-161h 08Learning Bayesian Statistics#56 Causal & Probabilistic Machine Learning, with Robert Osazuwa NessDid you know there is a relationship between the size of firetrucks and the amount of damage down to a flat during a fire? The bigger the truck sent to put out the fire, the bigger the damages tend to be. The solution is simple: just send smaller firetrucks!Wait, that doesn’t sound right, does it? Our brain is a huge causal machine, so it can instinctively feel it’s not credible that size of truck and amount of damage done are causally related: there must be another variable explaining the correlation. Here, it’s of course...
2022-02-161h 08
Learning Bayesian Statistics#55 Neuropsychology, Illusions & Bending Reality, with Dominique MakowskiWhat’s the common point between fiction, fake news, illusions and meditation? They can all be studied with Bayesian statistics, of course!In this mind-bending episode, Dominique Makowski will for sure expand your horizon. Trained as a clinical neuropsychologist, he is currently working as a postdoc at the Clinical Brain Lab in Singapore, in which he leads the Reality Bending Team. What’s reality-bending you ask? Well, you’ll have to listen to the episode, but I can already tell you we’ll go through a journey in scientific methodology, history of art, religion, and philosophy — what else?
2022-01-311h 13Learning Bayesian Statistics#55 Neuropsychology, Illusions & Bending Reality, with Dominique MakowskiWhat’s the common point between fiction, fake news, illusions and meditation? They can all be studied with Bayesian statistics, of course!In this mind-bending episode, Dominique Makowski will for sure expand your horizon. Trained as a clinical neuropsychologist, he is currently working as a postdoc at the Clinical Brain Lab in Singapore, in which he leads the Reality Bending Team. What’s reality-bending you ask? Well, you’ll have to listen to the episode, but I can already tell you we’ll go through a journey in scientific methodology, history of art, religion, and philosophy — what else?
2022-01-311h 13
Learning Bayesian Statistics#54 Bayes in Theoretical Ecology, with Florian HartigLet’s be honest: evolution is awesome! I started reading Improbable Destinies: Fate, Chance, and the Future of Evolution, by Jonathan Losos, and I’m utterly fascinated. So I’m thrilled to welcome Florian Hartig on the show. Florian is a professor of Theoretical Ecology at the University of Regensburg, Germany. His research concentrates on theory, computer simulations, statistical methods and machine learning in ecology & evolution. He is also interested in open science and open software development, and maintains, among other projects, the R packages DHARMa and BayesianTools.Among other things, we talked about approximate Bayesian...
2022-01-141h 08Learning Bayesian Statistics#54 Bayes in Theoretical Ecology, with Florian HartigLet’s be honest: evolution is awesome! I started reading Improbable Destinies: Fate, Chance, and the Future of Evolution, by Jonathan Losos, and I’m utterly fascinated. So I’m thrilled to welcome Florian Hartig on the show. Florian is a professor of Theoretical Ecology at the University of Regensburg, Germany. His research concentrates on theory, computer simulations, statistical methods and machine learning in ecology & evolution. He is also interested in open science and open software development, and maintains, among other projects, the R packages DHARMa and BayesianTools.Among other things, we talked about approximate Bayesian...
2022-01-141h 08
Learning Bayesian Statistics#53 Bayesian Stats for the Behavioral & Neural Sciences, with Todd HudsonGet a 30% discount on Todd's book by entering the code BDABNS22 at checkout!The behavioral and neural sciences are a nerdy interest of mine, but I didn’t dedicate any episode to that topic yet. But life brings you gifts sometimes (especially around Christmas…), and here that gift is a book, Bayesian Data Analysis for the Behavioral and Neural Sciences, by Todd Hudson.Todd is a part of the faculty at New York University Grossman School of Medicine and also the New York University Tandon School of Engineering. He is a computational neuroscientist working in seve...
2021-12-2856 minLearning Bayesian Statistics#53 Bayesian Stats for the Behavioral & Neural Sciences, with Todd HudsonGet a 30% discount on Todd's book by entering the code BDABNS22 at checkout!The behavioral and neural sciences are a nerdy interest of mine, but I didn’t dedicate any episode to that topic yet. But life brings you gifts sometimes (especially around Christmas…), and here that gift is a book, Bayesian Data Analysis for the Behavioral and Neural Sciences, by Todd Hudson.Todd is a part of the faculty at New York University Grossman School of Medicine and also the New York University Tandon School of Engineering. He is a computational neuroscientist working in seve...
2021-12-2856 min
Learning Bayesian Statistics#52 Election forecasting models in Germany, with Marcus GrossDid I mention I like survey data, especially in the context of electoral forecasting? Probably not, as I’m a pretty shy and reserved man. Why are you laughing?? Yeah, that’s true, I’m not that shy… but I did mention my interest for electoral forecasting already!And before doing a full episode where I’ll talk about French elections (yes, that’ll come at one point), let’s talk about one of France’s neighbors — Germany. Our German friends had federal elections a few weeks ago — consequential elections, since they had the hard task of replacing Angela Mer...
2021-12-0958 minLearning Bayesian Statistics#52 Election forecasting models in Germany, with Marcus GrossDid I mention I like survey data, especially in the context of electoral forecasting? Probably not, as I’m a pretty shy and reserved man. Why are you laughing?? Yeah, that’s true, I’m not that shy… but I did mention my interest for electoral forecasting already!And before doing a full episode where I’ll talk about French elections (yes, that’ll come at one point), let’s talk about one of France’s neighbors — Germany. Our German friends had federal elections a few weeks ago — consequential elections, since they had the hard task of replacing Angela Mer...
2021-12-0958 min
Learning Bayesian Statistics#51 Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey ClaytonYou know I love epistemology — the study of how we know what we know. It was high time I dedicated a whole episode to this topic. And what better guest than Aubrey Clayton, the author of the book Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science. I’m in the middle of reading it, and it’s a really great read!Aubrey is a mathematician in Boston who teaches the philosophy of probability and statistics at the Harvard Extension School. He holds a PhD in mathematics from the University of California, Berkeley, and his writing has ap...
2021-11-221h 09Learning Bayesian Statistics#51 Bernoulli’s Fallacy & the Crisis of Modern Science, with Aubrey ClaytonYou know I love epistemology — the study of how we know what we know. It was high time I dedicated a whole episode to this topic. And what better guest than Aubrey Clayton, the author of the book Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science. I’m in the middle of reading it, and it’s a really great read!Aubrey is a mathematician in Boston who teaches the philosophy of probability and statistics at the Harvard Extension School. He holds a PhD in mathematics from the University of California, Berkeley, and his writing has ap...
2021-11-221h 09
Learning Bayesian Statistics#50 Ta(l)king Risks & Embracing Uncertainty, with David SpiegelhalterFolks, this is the 50th episode of LBS — 50th! I never would have thought that there were so many Bayesian nerds in the world when I first interviewed Osvaldo Martin more than 2 years ago. To celebrate that random, crazy adventure, I wanted to do a special episode at any random point, and so it looks like it’s gonna be #50! This episode is special by its guest, not its number — although my guest knows a thing or two about numbers. Most recently, he wrote the book Covid by Numbers.A mathematical statistician dedicated to helping the gen...
2021-11-061h 04Learning Bayesian Statistics#50 Ta(l)king Risks & Embracing Uncertainty, with David SpiegelhalterFolks, this is the 50th episode of LBS — 50th! I never would have thought that there were so many Bayesian nerds in the world when I first interviewed Osvaldo Martin more than 2 years ago. To celebrate that random, crazy adventure, I wanted to do a special episode at any random point, and so it looks like it’s gonna be #50! This episode is special by its guest, not its number — although my guest knows a thing or two about numbers. Most recently, he wrote the book Covid by Numbers.A mathematical statistician dedicated to helping the gen...
2021-11-061h 04
Learning Bayesian Statistics#49 The Present & Future of Baseball Analytics, with Ehsan BokhariIt’s been a while since I did an episode about sports analytics, right? And you know it’s a field I love, so… let’s do that!For this episode, I was happy to host Ehsan Bokhari, not only because he’s a first-hour listener of the podcast and spread the word about it whenever he can, but mainly because he knows baseball analytics very well!Currently Senior Director of Strategic Decision Making with the Houston Astros, he previously worked there as Senior Director of Player Evaluation and Director of R&D. And before that, he w...
2021-10-221h 12Learning Bayesian Statistics#49 The Present & Future of Baseball Analytics, with Ehsan BokhariIt’s been a while since I did an episode about sports analytics, right? And you know it’s a field I love, so… let’s do that!For this episode, I was happy to host Ehsan Bokhari, not only because he’s a first-hour listener of the podcast and spread the word about it whenever he can, but mainly because he knows baseball analytics very well!Currently Senior Director of Strategic Decision Making with the Houston Astros, he previously worked there as Senior Director of Player Evaluation and Director of R&D. And before that, he w...
2021-10-221h 12
Learning Bayesian Statistics#48 Mixed Effects Models & Beautiful Plots, with TJ MahrIn episode 40, we already got a glimpse of how useful Bayesian stats are in the speech and communication sciences. To talk about the frontiers of this field (and, as it happens, about best practices to make beautiful plots and pictures), I invited TJ Mahr on the show.A speech pathologist turned data scientist, TJ earned his PhD in communication sciences and disorders in Madison, Wisconsin. On paper, he was studying speech development, word recognition and word learning in preschoolers, but over the course of his graduate training, he discovered that he really, really likes programming and working...
2021-10-081h 01Learning Bayesian Statistics#48 Mixed Effects Models & Beautiful Plots, with TJ MahrIn episode 40, we already got a glimpse of how useful Bayesian stats are in the speech and communication sciences. To talk about the frontiers of this field (and, as it happens, about best practices to make beautiful plots and pictures), I invited TJ Mahr on the show.A speech pathologist turned data scientist, TJ earned his PhD in communication sciences and disorders in Madison, Wisconsin. On paper, he was studying speech development, word recognition and word learning in preschoolers, but over the course of his graduate training, he discovered that he really, really likes programming and working...
2021-10-081h 01
Learning Bayesian Statistics#47 Bayes in Physics & Astrophysics, with JJ RubyThe field of physics has brought tremendous advances to modern Bayesian statistics, especially inspiring the current algorithms enabling all of us to enjoy the Bayesian power on our own laptops.I did receive some physicians already on the show, like Michael Betancourt in episode 6, but in my legendary ungratefulness I hadn’t dedicated a whole episode to talk about physics yet.Well that’s now taken care of, thanks to JJ Ruby. Apart from having really good tastes (he’s indeed a fan of this very podcast), JJ is currently a postdoctoral fellow for the Center...
2021-09-211h 15Learning Bayesian Statistics#47 Bayes in Physics & Astrophysics, with JJ RubyThe field of physics has brought tremendous advances to modern Bayesian statistics, especially inspiring the current algorithms enabling all of us to enjoy the Bayesian power on our own laptops.I did receive some physicians already on the show, like Michael Betancourt in episode 6, but in my legendary ungratefulness I hadn’t dedicated a whole episode to talk about physics yet.Well that’s now taken care of, thanks to JJ Ruby. Apart from having really good tastes (he’s indeed a fan of this very podcast), JJ is currently a postdoctoral fellow for the Center...
2021-09-211h 15
Learning Bayesian Statistics#46 Silly & Empowering Statistics, with Chelsea Parlett-PelleritiYou wanna know something funny? A sentence from this episode became a meme. And people even made stickers out of it! Ok, that’s not true. But if someone could pull off something like that, it would surely be Chelsea Parlett-Pelleriti.Indeed, Chelsea’s research focuses on using statistics and machine learning on behavioral data, but her more general goal is to empower people to be able to do their own statistical analyses, through consulting, education, and, as you may have seen, stats memes on Twitter.A full-time teacher, researcher and statistical consultant, Chelsea earned an M...
2021-08-301h 13Learning Bayesian Statistics#46 Silly & Empowering Statistics, with Chelsea Parlett-PelleritiYou wanna know something funny? A sentence from this episode became a meme. And people even made stickers out of it! Ok, that’s not true. But if someone could pull off something like that, it would surely be Chelsea Parlett-Pelleriti.Indeed, Chelsea’s research focuses on using statistics and machine learning on behavioral data, but her more general goal is to empower people to be able to do their own statistical analyses, through consulting, education, and, as you may have seen, stats memes on Twitter.A full-time teacher, researcher and statistical consultant, Chelsea earned an M...
2021-08-301h 13
Learning Bayesian Statistics#45 Biostats & Clinical Trial Design, with Frank HarrellAs a podcaster, I discovered that there are guests for which the hardest is to know when to stop the conversation. They could talk for hours and that would make for at least 10 fantastic episodes. Frank Harrell is one of those guests. To me, our conversation was both fascinating — thanks to Frank’s expertise and the width and depth of topics we touched on — and frustrating — I still had a gazillion questions for him!But rest assured, we talked about intent to treat and randomization, proportional odds, clinical trial design, bio stats and covid19, and even which mistakes...
2021-08-101h 08Learning Bayesian Statistics#45 Biostats & Clinical Trial Design, with Frank HarrellAs a podcaster, I discovered that there are guests for which the hardest is to know when to stop the conversation. They could talk for hours and that would make for at least 10 fantastic episodes. Frank Harrell is one of those guests. To me, our conversation was both fascinating — thanks to Frank’s expertise and the width and depth of topics we touched on — and frustrating — I still had a gazillion questions for him!But rest assured, we talked about intent to treat and randomization, proportional odds, clinical trial design, bio stats and covid19, and even which mistakes...
2021-08-101h 08
Learning Bayesian Statistics#44 Building Bayesian Models at scale, with Rémi LoufEpisode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21Bonjour my dear Bayesians! Yes, it was bound to happen one day — and this day has finally come. Here is the first ever 100% French speaking ‘Learn Bayes Stats’ episode! Who is to blame, you ask? Well, who better than Rémi Louf?Rémi currently works as a senior data scientist at Ampersand, a big media marketing company in the US. He is the author and maintainer of several open source libraries, including MCX and BlackJAX. He holds a PhD in...
2021-07-221h 15Learning Bayesian Statistics#44 Building Bayesian Models at scale, with Rémi LoufEpisode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21Bonjour my dear Bayesians! Yes, it was bound to happen one day — and this day has finally come. Here is the first ever 100% French speaking ‘Learn Bayes Stats’ episode! Who is to blame, you ask? Well, who better than Rémi Louf?Rémi currently works as a senior data scientist at Ampersand, a big media marketing company in the US. He is the author and maintainer of several open source libraries, including MCX and BlackJAX. He holds a PhD in...
2021-07-221h 15
Learning Bayesian Statistics#43 Modeling Covid19, with Michael Osthege & Thomas VladeckEpisode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21I don’t know if you’ve heard, but there is a virus that took over most of the world in the past year? I haven’t dedicated any episode to Covid yet. First because research was moving a lot — and fast. And second because modeling Covid is very, very hard.But we know more about it now, so I thought it was a good time to pause and ponder — how does the virus circulate? How can we model it a...
2021-07-081h 22Learning Bayesian Statistics#43 Modeling Covid19, with Michael Osthege & Thomas VladeckEpisode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21I don’t know if you’ve heard, but there is a virus that took over most of the world in the past year? I haven’t dedicated any episode to Covid yet. First because research was moving a lot — and fast. And second because modeling Covid is very, very hard.But we know more about it now, so I thought it was a good time to pause and ponder — how does the virus circulate? How can we model it a...
2021-07-081h 22
Learning Bayesian Statistics#42 How to Teach and Learn Bayesian Stats, with Mine DogucuEpisode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21We often talk about applying Bayesian statistics on this podcast. But how do we teach them? What’s the best way to introduce them from a young age and make sure the skills students learn in the stats class are transferable?Well, lucky us, Mine Dogucu’s research tackles precisely those topics!An Assistant Professor of Teaching in the Department of Statistics at University of California Irvine, Mine is both an educator with an interest in stat...
2021-06-241h 06Learning Bayesian Statistics#42 How to Teach and Learn Bayesian Stats, with Mine DogucuEpisode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21We often talk about applying Bayesian statistics on this podcast. But how do we teach them? What’s the best way to introduce them from a young age and make sure the skills students learn in the stats class are transferable?Well, lucky us, Mine Dogucu’s research tackles precisely those topics!An Assistant Professor of Teaching in the Department of Statistics at University of California Irvine, Mine is both an educator with an interest in stat...
2021-06-241h 06
Learning Bayesian Statistics#41 Thinking Bayes, with Allen DowneyLet’s think Bayes, shall we? And who better to do that than the author of the well known book, Think Bayes — Allen Downey himself! Since the second edition was just released, the timing couldn’t be better!Allen is a professor at Olin College and the author of books related to software and data science, including Think Python, Think Bayes, and Think Complexity. His blog, Probably Overthinking It, features articles on Bayesian probability and statistics. He holds a Ph.D. from U.C. Berkeley, and bachelors and masters degrees from MIT.In this special episod...
2021-06-141h 04Learning Bayesian Statistics#41 Thinking Bayes, with Allen DowneyLet’s think Bayes, shall we? And who better to do that than the author of the well known book, Think Bayes — Allen Downey himself! Since the second edition was just released, the timing couldn’t be better!Allen is a professor at Olin College and the author of books related to software and data science, including Think Python, Think Bayes, and Think Complexity. His blog, Probably Overthinking It, features articles on Bayesian probability and statistics. He holds a Ph.D. from U.C. Berkeley, and bachelors and masters degrees from MIT.In this special episod...
2021-06-141h 04
Learning Bayesian Statistics#40 Bayesian Stats for the Speech & Language Sciences, with Allison Hilger and Timo RoettgerWe all know about these accidental discoveries — penicillin, the heating power of microwaves, or the famous (and delicious) tarte tatin. I don’t know why, but I just love serendipity. And, as you’ll hear, this episode is deliciously full of it…Thanks to Allison Hilger and Timo Roettger, we’ll discover the world of linguistics, how Bayesian stats are helpful there, and how Paul Bürkner’s BRMS package has been instrumental in this field. To my surprise — and perhaps yours — the speech and language sciences are pretty quantitative and computational!As she recently discovered Bayesi...
2021-05-281h 05Learning Bayesian Statistics#40 Bayesian Stats for the Speech & Language Sciences, with Allison Hilger and Timo RoettgerWe all know about these accidental discoveries — penicillin, the heating power of microwaves, or the famous (and delicious) tarte tatin. I don’t know why, but I just love serendipity. And, as you’ll hear, this episode is deliciously full of it…Thanks to Allison Hilger and Timo Roettger, we’ll discover the world of linguistics, how Bayesian stats are helpful there, and how Paul Bürkner’s BRMS package has been instrumental in this field. To my surprise — and perhaps yours — the speech and language sciences are pretty quantitative and computational!As she recently discovered Bayesi...
2021-05-281h 05
Learning Bayesian Statistics#39 Survival Models & Biostatistics for Cancer Research, with Jacki BurosEpisode sponsored by Tidelift: tidelift.comIt’s been a while since we talked about biostatistics and bioinformatics on this podcast, so I thought it could be interesting to talk to Jacki Buros — and that was a very good idea!She’ll walk us through examples of Bayesian models she uses to, for instance, work on biomarker discovery for cancer immunotherapies. She’ll also introduce you to survival models — their usefulness, their powers and their challenges.Interestingly, all of this will highlight a handful of skills that Jacki would try to instill in her studen...
2021-05-1459 minLearning Bayesian Statistics#39 Survival Models & Biostatistics for Cancer Research, with Jacki BurosEpisode sponsored by Tidelift: tidelift.comIt’s been a while since we talked about biostatistics and bioinformatics on this podcast, so I thought it could be interesting to talk to Jacki Buros — and that was a very good idea!She’ll walk us through examples of Bayesian models she uses to, for instance, work on biomarker discovery for cancer immunotherapies. She’ll also introduce you to survival models — their usefulness, their powers and their challenges.Interestingly, all of this will highlight a handful of skills that Jacki would try to instill in her studen...
2021-05-1459 min
Learning Bayesian Statistics#38 How to Become a Good Bayesian (& Rap Artist), with Baba BrinkmanEpisode sponsored by Tidelift: tidelift.comImagine me rapping: "Let me show you how to be a good Bayesian. Change your predictions after taking information in, and if you’re thinking I’ll be less than amazing, let’s adjust those expectations!"What?? Nah, you’re right, I’m not as good as Baba Brinkman. Actually, the best to perform « Good Bayesian » live on the podcast would just be to invite him for an episode… Wait, isn’t that what I did???Well indeed! For this episode, I had the great pleasure of hosting rap artist...
2021-04-301h 27Learning Bayesian Statistics#38 How to Become a Good Bayesian (& Rap Artist), with Baba BrinkmanEpisode sponsored by Tidelift: tidelift.comImagine me rapping: "Let me show you how to be a good Bayesian. Change your predictions after taking information in, and if you’re thinking I’ll be less than amazing, let’s adjust those expectations!"What?? Nah, you’re right, I’m not as good as Baba Brinkman. Actually, the best to perform « Good Bayesian » live on the podcast would just be to invite him for an episode… Wait, isn’t that what I did???Well indeed! For this episode, I had the great pleasure of hosting rap artist...
2021-04-301h 27
Learning Bayesian Statistics#37 Prophet, Time Series & Causal Inference, with Sean TaylorEpisode sponsored by Tidelift: tidelift.comI don’t know about you, but the notion of time is really intriguing to me: it’s a purely artificial notion; we humans invented it — as an experiment, I asked my cat what time it was one day; needless to say it wasn’t very conclusive… And yet, the notion of time is so central to our lives — our work, leisures and projects depend on it.So much so that time series predictions represent a big part of the statistics and machine learning world. And to talk about all that, wh...
2021-04-161h 06Learning Bayesian Statistics#37 Prophet, Time Series & Causal Inference, with Sean TaylorEpisode sponsored by Tidelift: tidelift.comI don’t know about you, but the notion of time is really intriguing to me: it’s a purely artificial notion; we humans invented it — as an experiment, I asked my cat what time it was one day; needless to say it wasn’t very conclusive… And yet, the notion of time is so central to our lives — our work, leisures and projects depend on it.So much so that time series predictions represent a big part of the statistics and machine learning world. And to talk about all that, wh...
2021-04-161h 06
Learning Bayesian Statistics#36 Bayesian Non-Parametrics & Developing Turing.jl, with Martin TrappEpisode sponsored by Tidelift: tidelift.comI bet you already heard of Bayesian nonparametric models, at least on this very podcast. We already talked about Dirichlet Processes with Karin Knudson on episode 4, and then about Gaussian Processes with Elizaveta Semenova on episode 21. Now we’re gonna dive into the mathematical properties of these objects, to understand them better — because, as you may know, Bayesian nonparametrics are quite powerful but also very hard to fit!Along the way, you’ll learn about probabilistic circuits, sum-product networks and — what a delight — you’ll hear from the Julia community! I...
2021-03-301h 09Learning Bayesian Statistics#36 Bayesian Non-Parametrics & Developing Turing.jl, with Martin TrappEpisode sponsored by Tidelift: tidelift.comI bet you already heard of Bayesian nonparametric models, at least on this very podcast. We already talked about Dirichlet Processes with Karin Knudson on episode 4, and then about Gaussian Processes with Elizaveta Semenova on episode 21. Now we’re gonna dive into the mathematical properties of these objects, to understand them better — because, as you may know, Bayesian nonparametrics are quite powerful but also very hard to fit!Along the way, you’ll learn about probabilistic circuits, sum-product networks and — what a delight — you’ll hear from the Julia community! I...
2021-03-301h 09
Learning Bayesian Statistics#35 The Past, Present & Future of BRMS, with Paul BürknerEpisode sponsored by Tidelift: tidelift.comOne of the most common guest suggestions that you dear listeners make is… inviting Paul Bürkner on the show! Why? Because he’s a member of the Stan development team and he created BRMS, a popular R package to make and sample from Bayesian regression models using Stan. And, as I like you, I did invite Paul on the show and, well, that was a good call: we had an amazing conversation, spanning so many topics that I can’t list them all here!I asked him why he crea...
2021-03-121h 07Learning Bayesian Statistics#35 The Past, Present & Future of BRMS, with Paul BürknerEpisode sponsored by Tidelift: tidelift.comOne of the most common guest suggestions that you dear listeners make is… inviting Paul Bürkner on the show! Why? Because he’s a member of the Stan development team and he created BRMS, a popular R package to make and sample from Bayesian regression models using Stan. And, as I like you, I did invite Paul on the show and, well, that was a good call: we had an amazing conversation, spanning so many topics that I can’t list them all here!I asked him why he crea...
2021-03-121h 07
Learning Bayesian Statistics#34 Multilevel Regression, Post-stratification & Missing Data, with Lauren KennedyEpisode sponsored by Tidelift: tidelift.comWe already mentioned multilevel regression and post-stratification (MRP, or Mister P) on this podcast, but we didn’t dedicate a full episode to explaining how it works, why it’s useful to deal with non-representative data, and what its limits are. Well, let’s do that now, shall we?To that end, I had the delight to talk with Lauren Kennedy! Lauren is a lecturer in Business Analytics at Monash University in Melbourne, Australia, where she develops new statistical methods to analyze social science data. Working mainly with R and St...
2021-02-251h 12Learning Bayesian Statistics#34 Multilevel Regression, Post-stratification & Missing Data, with Lauren KennedyEpisode sponsored by Tidelift: tidelift.comWe already mentioned multilevel regression and post-stratification (MRP, or Mister P) on this podcast, but we didn’t dedicate a full episode to explaining how it works, why it’s useful to deal with non-representative data, and what its limits are. Well, let’s do that now, shall we?To that end, I had the delight to talk with Lauren Kennedy! Lauren is a lecturer in Business Analytics at Monash University in Melbourne, Australia, where she develops new statistical methods to analyze social science data. Working mainly with R and St...
2021-02-251h 12
Mind Education PodcastPoftă de viață. Cu Claudia Buneci. Mind about You (Ep. 22)Europa este continentul cel mai puternic afectat de bolile cronice non-contagioase iar creșterea incidenței lor este alarmantă, consideră Organizația Mondială a Sănătății. Aceste boli sunt responsabile pentru 86% dintre decesele din Europa și pentru 77% din costurile directe și indirecte asupra sistemelor medicale și a sănătății publice. Bolile infecțioase afectează în prezent mult mai puțini oameni decât cele netransmisibile. De aceea avem nevoie de schimbarea de mentalitate de la tratarea bolii la îngrijirea personală. Iar aceasta vine cu schimbări ale stilului de viață și mai ales cu conștientizarea faptului că acest...
2021-02-1534 min
Learning Bayesian Statistics#33 Bayesian Structural Time Series, with Ben ZweigHow do people choose their career? How do they change jobs? How do they even change careers? These are important questions that we don’t have great answers to. But structured data about the dynamics of labor markets are starting to emerge, and that’s what Ben Zweig is modeling at Revelio Labs.An economist and data scientist, Ben is indeed the CEO of Revelio Labs, a data science company analyzing raw labor data contained in resumes, online profiles and job postings. In this episode, he’ll tell us about the Bayesian structural time series model they built...
2021-02-1257 minLearning Bayesian Statistics#33 Bayesian Structural Time Series, with Ben ZweigHow do people choose their career? How do they change jobs? How do they even change careers? These are important questions that we don’t have great answers to. But structured data about the dynamics of labor markets are starting to emerge, and that’s what Ben Zweig is modeling at Revelio Labs.An economist and data scientist, Ben is indeed the CEO of Revelio Labs, a data science company analyzing raw labor data contained in resumes, online profiles and job postings. In this episode, he’ll tell us about the Bayesian structural time series model they built...
2021-02-1257 min
Learning Bayesian Statistics#32 Getting involved into Bayesian Stats & Open-Source Development, with Peadar CoyleWhen explaining Bayesian statistics to people who don’t know anything about stats, I often say that MCMC is about walking many different paths in lots of parallel universes, and then counting what happened in all these universes.And in a sense, this whole podcast is dedicated to sampling the whole distribution of Bayesian practitioners. So, for this episode, I thought we’d take a break of pure, hard modeling and talk about how to get involved into Bayesian statistics and open-source development, how companies use Bayesian tools, and what common struggles and misperceptions the latter suffer from...
2021-01-2753 minLearning Bayesian Statistics#32 Getting involved into Bayesian Stats & Open-Source Development, with Peadar CoyleWhen explaining Bayesian statistics to people who don’t know anything about stats, I often say that MCMC is about walking many different paths in lots of parallel universes, and then counting what happened in all these universes.And in a sense, this whole podcast is dedicated to sampling the whole distribution of Bayesian practitioners. So, for this episode, I thought we’d take a break of pure, hard modeling and talk about how to get involved into Bayesian statistics and open-source development, how companies use Bayesian tools, and what common struggles and misperceptions the latter suffer from...
2021-01-2753 min
Learning Bayesian Statistics#31 Bayesian Cognitive Modeling & Decision-Making, with Michael LeeI don’t know if you noticed, but I have a fondness for any topic related to decision-making under uncertainty — when it’s studied scientifically of course. Understanding how and why people make decisions when they don’t have all the facts is fascinating to me. That’s why I like electoral forecasting and I love cognitive sciences.So, for the first episode of 2021, I have a special treat: I had the great pleasure of hosting Michael Lee on the podcast! Yes, the Michael Lee who co-authored the book Bayesian Cognitive Modeling with Eric-Jan Wagenmakers in 2013 — by the way, the...
2021-01-051h 09Learning Bayesian Statistics#31 Bayesian Cognitive Modeling & Decision-Making, with Michael LeeI don’t know if you noticed, but I have a fondness for any topic related to decision-making under uncertainty — when it’s studied scientifically of course. Understanding how and why people make decisions when they don’t have all the facts is fascinating to me. That’s why I like electoral forecasting and I love cognitive sciences.So, for the first episode of 2021, I have a special treat: I had the great pleasure of hosting Michael Lee on the podcast! Yes, the Michael Lee who co-authored the book Bayesian Cognitive Modeling with Eric-Jan Wagenmakers in 2013 — by the way, the...
2021-01-051h 09
Learning Bayesian Statistics#30 Symbolic Computation & Dynamic Linear Models, with Brandon WillardIt’s funny how powerful symbols are, right? The Eiffel Tower makes you think of Paris, the Statue of Liberty is New-York, and the Trevi Fountain… is Rome of course! Just with one symbol, you can invoke multiple concepts and ideas.You probably know that symbols are omnipresent in mathematics — but did you know that they are also very important in statistics, especially probabilistic programming?Rest assured, I didn’t really know either… until I talked with Brandon Willard! Brandon is indeed a big proponent of relational programming and symbolic computation, and he often promotes their use...
2020-12-181h 00Learning Bayesian Statistics#30 Symbolic Computation & Dynamic Linear Models, with Brandon WillardIt’s funny how powerful symbols are, right? The Eiffel Tower makes you think of Paris, the Statue of Liberty is New-York, and the Trevi Fountain… is Rome of course! Just with one symbol, you can invoke multiple concepts and ideas.You probably know that symbols are omnipresent in mathematics — but did you know that they are also very important in statistics, especially probabilistic programming?Rest assured, I didn’t really know either… until I talked with Brandon Willard! Brandon is indeed a big proponent of relational programming and symbolic computation, and he often promotes their use...
2020-12-181h 00
Learning Bayesian Statistics#29 Model Assessment, Non-Parametric Models, And Much More, with Aki VehtariI’ll be honest here: I had a hard time summarizing this episode for you, and, let’s face it, it’s all my guest’s fault! Why? Because Aki Vehtari works on so many interesting projects that it’s hard to sum them all up, even more so because he was very generous with his time for this episode! But let’s try anyway, shall we?So, Aki is an Associate professor in computational probabilistic modeling at Aalto University, Finland. You already heard his delightful Finnish accent on episode 20, with Andrew Gelman and Jennifer Hill, talking about their...
2020-12-021h 05Learning Bayesian Statistics#29 Model Assessment, Non-Parametric Models, And Much More, with Aki VehtariI’ll be honest here: I had a hard time summarizing this episode for you, and, let’s face it, it’s all my guest’s fault! Why? Because Aki Vehtari works on so many interesting projects that it’s hard to sum them all up, even more so because he was very generous with his time for this episode! But let’s try anyway, shall we?So, Aki is an Associate professor in computational probabilistic modeling at Aalto University, Finland. You already heard his delightful Finnish accent on episode 20, with Andrew Gelman and Jennifer Hill, talking about their...
2020-12-021h 05
Learning Bayesian Statistics#28 Game Theory, Industrial Organization & Policy Design, with Shosh VassermanIn times of crisis, designing an efficient policy response is paramount. In case of natural disasters or pandemics, it can even determine the difference between life and death for a substantial number of people. But precisely, how do you design such policy responses, making sure that risks are optimally shared, people feel safe enough to reveal necessary information, and stakeholders commit to the policies?That’s where a field of economics, industrial organization (IO), can help, as Shosh Vasserman will tell us in this episode. Shosh is an assistant professor of economics at the Stanford Graduate School of...
2020-11-201h 03Learning Bayesian Statistics#28 Game Theory, Industrial Organization & Policy Design, with Shosh VassermanIn times of crisis, designing an efficient policy response is paramount. In case of natural disasters or pandemics, it can even determine the difference between life and death for a substantial number of people. But precisely, how do you design such policy responses, making sure that risks are optimally shared, people feel safe enough to reveal necessary information, and stakeholders commit to the policies?That’s where a field of economics, industrial organization (IO), can help, as Shosh Vasserman will tell us in this episode. Shosh is an assistant professor of economics at the Stanford Graduate School of...
2020-11-201h 03
Learning Bayesian Statistics#25 Bayesian Stats in Football Analytics, with Kevin MinkusHave you watched the series « The English Game », on Netflix? Well, I think you should — it’s a fascinating dive into how football went from an aristocratic to a popular sport in the late 19th century England. Today it is so popular that it became a valuable business to do statistics on the game and its players!To talk about that, I invited Kevin Minkus on the show — he’s a data scientist and soccer fan living in Philadelphia. Kevin’s currently working at Monetate on ecommerce problems, and prior to Monetate he worked on property and casualty insur...
2020-10-0955 minLearning Bayesian Statistics#25 Bayesian Stats in Football Analytics, with Kevin MinkusHave you watched the series « The English Game », on Netflix? Well, I think you should — it’s a fascinating dive into how football went from an aristocratic to a popular sport in the late 19th century England. Today it is so popular that it became a valuable business to do statistics on the game and its players!To talk about that, I invited Kevin Minkus on the show — he’s a data scientist and soccer fan living in Philadelphia. Kevin’s currently working at Monetate on ecommerce problems, and prior to Monetate he worked on property and casualty insur...
2020-10-0955 min
Learning Bayesian Statistics#24 Bayesian Computational Biology in Julia, with Seth AxenDo you know what proteins are, what they do and why they are useful? Well, be prepared to be amazed! In this episode, Seth Axen will tell us about the fascinating world of protein structures and computational biology, and how his work of Bayesian modeler fits into that!Passionate about mathematics and statistics, Seth is finishing a PhD in bioinformatics at the Sali Lab of the University of California, San Francisco (UCSF). His research interests span the broad field of computational biology: using computer science, mathematics, and statistics to understand biological systems. His current research focuses on...
2020-09-2456 minLearning Bayesian Statistics#24 Bayesian Computational Biology in Julia, with Seth AxenDo you know what proteins are, what they do and why they are useful? Well, be prepared to be amazed! In this episode, Seth Axen will tell us about the fascinating world of protein structures and computational biology, and how his work of Bayesian modeler fits into that!Passionate about mathematics and statistics, Seth is finishing a PhD in bioinformatics at the Sali Lab of the University of California, San Francisco (UCSF). His research interests span the broad field of computational biology: using computer science, mathematics, and statistics to understand biological systems. His current research focuses on...
2020-09-2456 min
Learning Bayesian Statistics#22 Eliciting Priors and Doing Bayesian Inference at Scale, with Avi BryantIf, like me, you’ve been stuck in a 40 square-meter apartment for two months, you’re going to be pretty jealous of Avi Bryant. Indeed, Avi lives on Galiano Island, Canada, not very far from Vancouver, surrounded by forest, overlooking the Salish Sea. In this natural and beautiful — although slightly deer-infested — spot, Avi runs The Gradient Retreat Center, a place where writers, makers, and code writers can take a week away from their regular lives and focus on creative work. But it’s not only to envy him that I invited Avi on the show — it’s to talk about B...
2020-08-261h 06Learning Bayesian Statistics#22 Eliciting Priors and Doing Bayesian Inference at Scale, with Avi BryantIf, like me, you’ve been stuck in a 40 square-meter apartment for two months, you’re going to be pretty jealous of Avi Bryant. Indeed, Avi lives on Galiano Island, Canada, not very far from Vancouver, surrounded by forest, overlooking the Salish Sea. In this natural and beautiful — although slightly deer-infested — spot, Avi runs The Gradient Retreat Center, a place where writers, makers, and code writers can take a week away from their regular lives and focus on creative work. But it’s not only to envy him that I invited Avi on the show — it’s to talk about B...
2020-08-261h 06
Learning Bayesian Statistics#19 Turing, Julia and Bayes in Economics, with Cameron PfifferDo you know Turing? Of course you do! With Soss and Gen, it’s one of the blockbusters to do probabilistic programming in Julia. And in this episode Cameron Pfiffer will tell us all about it — how it came to life, how it fits into the probabilistic programming landscape, and what its main strengths and weaknesses are.Cameron did some Rust, some Python, but he especially loves coding in Julia. That’s also why he’s one of the core-developers of Turing.jl. He’s also a PhD student in finance at the University of Oregon and did his ma...
2020-07-031h 00Learning Bayesian Statistics#19 Turing, Julia and Bayes in Economics, with Cameron PfifferDo you know Turing? Of course you do! With Soss and Gen, it’s one of the blockbusters to do probabilistic programming in Julia. And in this episode Cameron Pfiffer will tell us all about it — how it came to life, how it fits into the probabilistic programming landscape, and what its main strengths and weaknesses are.Cameron did some Rust, some Python, but he especially loves coding in Julia. That’s also why he’s one of the core-developers of Turing.jl. He’s also a PhD student in finance at the University of Oregon and did his ma...
2020-07-031h 00