Learning Bayesian Statistics
A podcast by Alexandre Andorra
Categories:
120 Episodes
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#105 The Power of Bayesian Statistics in Glaciology, with Andy Aschwanden & Doug Brinkerhoff
Published: 5/2/2024 -
#104 Automated Gaussian Processes & Sequential Monte Carlo, with Feras Saad
Published: 4/16/2024 -
#103 Improving Sampling Algorithms & Prior Elicitation, with Arto Klami
Published: 4/5/2024 -
#102 Bayesian Structural Equation Modeling & Causal Inference in Psychometrics, with Ed Merkle
Published: 3/20/2024 -
How to find black holes with Bayesian inference
Published: 3/16/2024 -
How can we even hear gravitational waves?
Published: 3/14/2024 -
#101 Black Holes Collisions & Gravitational Waves, with LIGO Experts Christopher Berry & John Veitch
Published: 3/7/2024 -
The Role of Variational Inference in Reactive Message Passing
Published: 3/1/2024 -
Reactive Message Passing in Bayesian Inference
Published: 2/28/2024 -
#100 Reactive Message Passing & Automated Inference in Julia, with Dmitry Bagaev
Published: 2/21/2024 -
The biggest misconceptions about Bayes & Quantum Physics
Published: 2/16/2024 -
Why would you use Bayesian Statistics?
Published: 2/14/2024 -
#99 Exploring Quantum Physics with Bayesian Stats, with Chris Ferrie
Published: 2/9/2024 -
How do sampling algorithms scale?
Published: 2/5/2024 -
Why choose new algorithms instead of HMC?
Published: 2/4/2024 -
#98 Fusing Statistical Physics, Machine Learning & Adaptive MCMC, with Marylou Gabrié
Published: 1/24/2024 -
Why Even Care About Science & Rationality
Published: 1/20/2024 -
How To Get Into Causal Inference
Published: 1/17/2024 -
#97 Probably Overthinking Statistical Paradoxes, with Allen Downey
Published: 1/9/2024 -
How to Choose & Use Priors, with Daniel Lee
Published: 12/20/2023
Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is? Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow. When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created "Learning Bayesian Statistics", where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped. But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners! My name is Alex Andorra by the way, and I live in Estonia. By day, I'm a data scientist and modeler at the PyMC Labs consultancy. By night, I don't (yet) fight crime, but I'm an open-source enthusiast and core contributor to the python packages PyMC and ArviZ. I also love election forecasting and, most importantly, Nutella. But I don't like talking about it – I prefer eating it. So, whether you want to learn Bayesian statistics or hear about the latest libraries, books and applications, this podcast is for you -- just subscribe! You can also support the show and unlock exclusive Bayesian swag on Patreon!
