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

🎧 https://lnkd.in/gAX2iaHz

#bayesianinference

🎙️ 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

🎧 https://lnkd.in/geA2kQm6

#Bayesian #LearningBayesianStats

🎙️ What does it take to grow in tech? Jordan Thibodeau shares lessons from years inside top tech cultures with Alex Andorra

✅ Bayesian thinking as a practical advantage

✅ AI amplifies skill, not replaces it

✅ Networking & sharing knowledge matter

🎧 https://lnkd.in/ghk6D6nH

#bayes #career

Bayesian deep learning helps ML models understand their uncertainty

In this episode Alex Andorra talks with Maurizio Filippone about Gaussian Processes, scalable inference, MCMC, and Bayesian deep learning at scale

🎧 https://learnbayesstats.com/episode/144-why-is-bayesian-deep-learning-so-powerful-maurizio-filippone

#BayesianStats #AI #ML #Bayes

🍽️ Can better nutrition science come from better statistics?

In the latest episode, Alex Andorra chats with Christoph Bamberg about using a Bayesian mindset to make psychology & nutrition research more transparent and actionable

🎧 https://learnbayesstats.com/episode/143-transforming-nutrition-science-bayesian-methods-christoph-bamberg

#bayes #nutrition

🤔How do you keep Bayesian rigor when the data’s too big to behave?

Gabriel Stechschulte joins Alex Andorra on Learning Bayesian Statistics to talk BART and how they’re bridging classic stats with modern, large-scale systems.

🎧 Listen here: https://learnbayesstats.com/episode/142-bayesian-trees-deep-learning-optimization-big-data-gabriel-stechschulte

🧪 Causal inference is about understanding why things happen, not just what

Alex Andorra talks with Sam Witty about ChiRho & how probabilistic programming is reshaping interventions, counterfactuals, and the future of causal reasoning

🎧https://learnbayesstats.com/episode/141-ai-assisted-causal-inference-sam-witty

#CausalInference #BayesianStatistics #Podcast #DataScience #AIResearch #LearningBayesianStatistics #NewEpisode

🏈 NFL meets Bayesian stats!

In this episode Alex Andorra chats with Ron Yurko on

👉 Writing your own models
👉 Building a sports analytics portfolio
👉 Pitfalls of modelling expectations
👉 Using tracking data for player insights
👉 Causal thinking in football data

🎧 https://lnkd.in/gWz4v2JG

#bayesian #podcast #learningbayesianstatistics #SportsAnalytics #NFL #statistics

What if your optimization algorithm could explain its uncertainty as clearly as its results?” 🤔

In this episode🎙️ Alex Andorra dives into Bayesian optimization, BoTorch, and why uncertainty matters with Maximilian Balandat

🎧 Listen here: https://lnkd.in/gg6fcfFU

#bayesian #pytorch #podcast

Your deep learning model might be confidently wrong — and in medicine or epidemiology, that’s dangerous.

In this episode, Alex Andorra chats with Mélodie Monod, François-Xavier & Yingzhen Li about making neural nets more reliable, Bayesian LLMs & more...

🎧 https://lnkd.in/gcaRQXcb

#bayes #llm