Learning Bayesian Statistics
Een podcast door Alexandre Andorra - Woensdagen
Categorieën:
145 Afleveringen
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#110 Unpacking Bayesian Methods in AI with Sam Duffield
Gepubliceerd: 10-7-2024 -
#109 Prior Sensitivity Analysis, Overfitting & Model Selection, with Sonja Winter
Gepubliceerd: 25-6-2024 -
#108 Modeling Sports & Extracting Player Values, with Paul Sabin
Gepubliceerd: 14-6-2024 -
#107 Amortized Bayesian Inference with Deep Neural Networks, with Marvin Schmitt
Gepubliceerd: 29-5-2024 -
#106 Active Statistics, Two Truths & a Lie, with Andrew Gelman
Gepubliceerd: 16-5-2024 -
#105 The Power of Bayesian Statistics in Glaciology, with Andy Aschwanden & Doug Brinkerhoff
Gepubliceerd: 2-5-2024 -
#104 Automated Gaussian Processes & Sequential Monte Carlo, with Feras Saad
Gepubliceerd: 16-4-2024 -
#103 Improving Sampling Algorithms & Prior Elicitation, with Arto Klami
Gepubliceerd: 5-4-2024 -
#102 Bayesian Structural Equation Modeling & Causal Inference in Psychometrics, with Ed Merkle
Gepubliceerd: 20-3-2024 -
How to find black holes with Bayesian inference
Gepubliceerd: 16-3-2024 -
How can we even hear gravitational waves?
Gepubliceerd: 14-3-2024 -
#101 Black Holes Collisions & Gravitational Waves, with LIGO Experts Christopher Berry & John Veitch
Gepubliceerd: 7-3-2024 -
The Role of Variational Inference in Reactive Message Passing
Gepubliceerd: 1-3-2024 -
Reactive Message Passing in Bayesian Inference
Gepubliceerd: 28-2-2024 -
#100 Reactive Message Passing & Automated Inference in Julia, with Dmitry Bagaev
Gepubliceerd: 21-2-2024 -
The biggest misconceptions about Bayes & Quantum Physics
Gepubliceerd: 16-2-2024 -
Why would you use Bayesian Statistics?
Gepubliceerd: 14-2-2024 -
#99 Exploring Quantum Physics with Bayesian Stats, with Chris Ferrie
Gepubliceerd: 9-2-2024 -
How do sampling algorithms scale?
Gepubliceerd: 5-2-2024 -
Why choose new algorithms instead of HMC?
Gepubliceerd: 4-2-2024
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!
