A #podcast on #Bayesian #Statistics -- the methods, the projects, the people
By Alexandre Andorra
#StatsTodon #BayesianStats #Science
| Listen | https://learnbayesstats.com/ |
| Support | https://t.co/K2sP6W7Eug |
| https://www.linkedin.com/company/learn-bayes-stats/ | |
| Blue Sky | https://bsky.app/profile/learnbayesstats.bsky.social |
🎙️ New episode alert!
In this episode Alex Andorra & Stefan Radev dive into amortized inference, train a neural net once on sims, deploy on real data as many times as you want. They cover sim-to-real, psych & neuro as test beds, honest failure modes and more ...
Most stats thinking starts with a dataset.
Bayesian experimental design asks: which data should you collect first?
Ep 156 of Learning Bayesian Statistics with Alex Andorra and Adam Foster covers:
👉Expected information gain
👉BALD
👉Deep adaptive design and more ...
#BayesianStatistics #ExperimentalDesign #BayesianInference #ActiveLearning
🎙️ New episode of Learning Bayesian Statistics!
EP 155 with Alex Andorra & Andreas Munk, why Bayesian inference still hasn't broken into everyday use. The barrier isn't the math, it's the mental shift
Episode 152 is out 🎙️
Host Alex Andorra talks with Daniel Saunders about a Bayesian decision theory workflow.
Big idea: stop optimizing for model accuracy and start optimizing for decision value.
🎙️ New episode out now - Episode 151: Diffusion Models in Python, a Live Demo
In this episode, Alex Andorra is joined by Jonas Arruda to explore how diffusion models can be used for simulation-based inference (SBI) in practice with a live Python demo and more ...
Bayesian neural networks need one thing to matter: good uncertainty. Scaling them has always been the hard part
In this episode, host Alex Andorra with Emmanuel Sommer, Jakob Robnik, and David Rügamer explain what’s changing, faster sampling, better dynamics & more ...
Work in tech is changing fast, and not always in obvious ways.
Alex Andorra talks with Alana Karen about how AI, hiring, and management are reshaping careers behind the scenes, AI automating early work, hiring favoring familiarity … and more.
Clinical trials don’t fail because patients fail.
They fail when designs stop learning.
Episode 148 of Learning Bayesian Statistics explores adaptive & platform trials and why "wait for the final analysis" isn’t neutral in ALS or pandemics.
Fast Bayesian inference is great… until you’re babysitting convergence.
Alex Andorra is joined by Martin Ingram to explore DADVI a more predictable, less noisy approach to variational inference that makes trade-offs explicit instead of mysterious
🎙️ How do you tackle extreme physics experiments? Ethan Smith shares insights with Alex Andorra
✅ Bayesian inference for sparse, noisy data
✅ Priors guide well-established physical models
✅ Scaling Bayesian workflows across teams
