Big update to my #BayesianWorkflow and #CausalInference #AgentSkills ! Now teach PyMC 6 + ArviZ 1.0 first-class -- the latest best practices, baked in -- while still running on PyMC 5 if you can't upgrade yet. Your AI agent should know the newest idioms! github.com/Learning-Bay...

Second part of my conversation with Stefan Radev is out, my dear Bayesians! We dive deep into how simulations improve #Bayesian workflows, how to do cheap #sensitivity and #multiverse analysis, and where #BayesFlow is headed next. Enjoy!

Latest episode is out, my dear #Bayesians! A deep dive into #AmortizedInference, what it looks like in practice, and how to teach it to your AI agents. Tune if you wanna see how to do fast, amortized inference that scales -- live, demoed by Stefan 😉

New episode is out forks! BALD, BED and other fun academic acronyms 😏

New episode is out! I sit down with Andreas Munk to explore one of the most important -- and most underappreciated -- tensions in modern Bayesian practice: the gap between what we can do in research and what actually gets deployed in the wild. Hope you like it!

⚽ Last week, I was thrilled and honored to present our #SoccerFactorModel to Field of Play 2026 in Manchester! 🎙️ It was an absolute blast meeting all these brilliant people, and I can't thank enough the FoP team, especially Dominic Jordan and John Carney for their trust and invitation! 🧵 Thread 👇

Wrote up the full story behind the #CausalInference agent skill. Key insight: agents *know* causal inference, but they never stop to ask "is my DAG right?" or "does this survive a placebo test?" The skill doesn't add knowledge. It adds discipline. Full breakdown: learnbayesstats.com/blog-posts/c...

Just released a new #AgentSkill: causal inference that refuses to say "causes" until it's earned the right. DAG before data. Assumptions before estimates. Refutation before claims. 100% eval pass rate vs 68% without the skill. The gap is in the reasoning, not the code. 👉 github.com/Learning-Bay...

New episode is out, my dear Bayesians! All about #CausalInference, #Experimentation at scale, and #GaussianProcesses -- definitely a fun one!

The show now has a blog section 🍾 Check out @alex-andorra.bsky.social 's first post!

2 weeks ago, I published my #BayesianWorkflowSkill, which scored 100% on evals. Then, the brilliant Max Göbel actually used it on a real model. And it broke 🤨 Lesson: evals are necessary, but not sufficient. Get your tools into real hands early! Full blog post: learnbayesstats.com/blog-posts/b...

I taught my coding agent to think like a Bayesian, and wrote up what I learned. LLMs know #BayesianStats but skip half the workflow. So I built an open-source Agent Skill that enforces the full workflow every time Works with Claude Code, Cursor, Gemini, etc. learnbayesstats.com/blog-posts/b...

New episode is out 🍾

at my job I’m expectedutilitymaxxing. I chatted with @alex-andorra.bsky.social on how to make it scalable and fast in an industrial context on top of the probabilistic programming language you already love, PyMC.

Just published my first open-source #AgentSkill! It's called bayesian-workflow, and helps you do #BayesianAnaylsis the right way -- well, at least I hope... Check it out here: github.com/Learning-Bay...

New episode is out, where we dive into how to use #ProbabilisticModel to do #DecisionMakingOptimization -- because the best model is useless if you can't make decision from it. See you in there!

Diffusion models & flow matching are reshaping simulation-based inference. Thus, we wrote the first tutorial review on diffusion-based SBI. For an overview or a deep dive, check it out and let us know what you think: arXiv: arxiv.org/abs/2512.20685 Web: bayesflow-org.github.io/diffusion-ex...

My #AdvancedRegressionModeling course, written with the brilliant Ravin Kumar and @tomicapretto.bsky.social, is now available through my Topmate profile! So do give it a try and let me know what you think in the comments 👇 See you soon in the Intuitive Bayes' Discourse 🖖 topmate.io/alex_andorra...

I don't code anymore—I build. AI lets me ship projects by describing what I want, not how to do it. In 10 days, I shipped 6 projects with OpenCode + Claude Opus 4.5. The gap between idea and product is tiny now. Would you try this? Repost or comment! buff.ly/blroW24 #ai #buildfast

This one is a foundational one: #ExperimentalTrialDesign the ̶r̶i̶g̶h̶t̶ Bayesian way, with no other than Scott Berry, from Berry Consultants, LLC! Enjoy, and happy new year, my dear Bayesians 🖖

Very practical episode this week: What to do when you can't use MCMC but still want #BayesPerks? Well, Deterministic ADVI is the new kid on the block, and is a pretty cool one ;) #WhoisyourDADVInow

🎙️ How do you tackle extreme physics experiments? Ethan Smith shares insights with @alex-andorra.bsky.social ✅ Bayesian inference for sparse, noisy data ✅ Priors guide well-established physical models ✅ Scaling Bayesian workflows across teams 🎧 lnkd.in/geA2kQm6 #Bayesian #LearningBayesianStats

Time to take stock of what is going on in the #TechIndustry, how #GenAI is changing the jobs, and how to integrate it in your career. Here is a super dense, and hopefully actionable, episode with the great Jordan Thibodeau -- make sure to give his SVIC Podcast a listen!

This one is a very practical one, with the great Maurizio Filippone -- all about the intersection of #DeepLearning , #GaussianProcesses and why combining them is so powerful. Enjoy!

🍽️ Can better nutrition science come from better statistics? In the latest episode, @alex-andorra.bsky.social chats with Christoph Bamberg about using a Bayesian mindset to make psychology & nutrition research more transparent and actionable 🎧 learnbayesstats.com/episode/143-... #bayes #nutrition

How to run #BART and #TreeModels fast in #Python -- new episode is out, with @gstechschulte.bsky.social !

🏈 NFL meets Bayesian stats! In this episode @alex-andorra.bsky.social 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 🎧 lnkd.in/gWz4v2JG

Really enjoyed talking to @alex-andorra.bsky.social on @learnbayesstats.bsky.social! I've always enjoyed listening to this podcast and encourage you to check out all of the awesome episodes Alex has recorded: learnbayesstats.com #statistics #Bayesian #datascience #sportsanalytics

Really recommend this one, about how to blend #CausalInference and #DeepLearning in practice, with ChiRho and Pyro!

This was a super fun one, geeking out on LLMs, deep neural nets and optimization with Maximilian Balandat, from Meta

Live episode from @imperialcollegeldn.bsky.social is out! All about #BayesianDeepLearning

🚨 MCMC or INLA? 🤯 MCMC = slow sampling. ⚡ INLA = fast, smart approximations. No chains, no waiting. 🎙️ On LBS, @alex-andorra.bsky.social talks with Haavard Rue & Janet Van Niekerk about how INLA works, when to use it, and why it’s a game-changer. 🎧 Listen: lnkd.in/gp8D-RuU #Bayesian #MCMC

New episode is out! A really fascinating one with Robert Ness, about his new #CausalAI book, which actually kickstarted a whole new learning path for me Robert and I are actually working on an educational project you're gonna love... Follow @learnbayesstats.bsky.social for the upcoming announcement!

New episode is out, about how to scale #BayesianInference to #BigData and #BigModels!

Came across this 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝘁 𝗲𝘅𝗮𝗺𝗽𝗹𝗲 using the 𝗛𝗼𝗿𝘀𝗲𝘀𝗵𝗼𝗲 𝗣𝗿𝗶𝗼𝗿 — a powerful Bayesian tool for #SparseRegression — via the @pymc.io & Bambi ecosystem, so wanted to share it with you folks! A big thanks to @aloctavodia.bsky.social & @tomicapretto.bsky.social for their great and continued work on this 🙏

Really looking forward to teaching a new PyMC tutorial, with the great Jesse Grabowski at PyData Berlin! We'll teach how to do #StateSpaceModeling with @pymc.io -- and developing some new features just for this 😉 Come say hi if you're in Berlin September 1-3! berlin.pydata.org/conferences/...

New episode is out! A very practical one, where we dive into *how* to make sure your models *actually* answer the questions you're asking...

ICYMI, I'll be in London next week, for a #LiveEpisode of the @learnbayesstats.bsky.social 🍾 Come say hi on June 24 at Imperial College London! We'll be talking about uncertainty quantification. 🎟️ www.eventbrite.co.uk/e/machine-le...

🎲 Bayesian Nerds Assemble! 🎲 Live panel on "Machine Learning & Uncertainty" at Imperial College London, June 24. I'm hosting, joined by Mélodie Monod, Yingzhen Li, and FX Briol. Probability you'll have fun: extremely high! Sign up before uncertainty sets in: www.eventbrite.co.uk/e/machine-le...

New episode is out! We covered some of the most practical and under-discussed tools in #Bayesian econometrics: 🔷 #DynamicRegression 🔷 #StateSpaceModels 🔷 Predictively consistent priors 🔷 Bayesian R² 🔷 Whether AI could help us elicit better priors

New episode is out! In this one we nerd out quite deep on zero-sum constraints, and how to make your model sample faster 💨

New episode is out, where dive into how human brains work, and how this compares to #ArtificialIntelligence

New episode is out, where we dive into how to actually make tough decisions once you have built, fit, and validated your Bayesian models 🤔

🚨 LIVE SHOW ALERT 🚨 If you're a Patron, join us tomorrow April 24, 11:00am, US Eastern Time, with David Kohns, co-author of "The ARR2 Prior: Flexible Predictive Prior Definition for Bayesian Auto-Regressions" 🥳 👉 Patreon: www.patreon.com/c/learnbayes... 👉 YouTube: www.youtube.com/@learningbay...

New episode just dropped! All about #EpidemiologicalModeling, #ScienceCommunication and #Epistemology

It was a great pleasure to host @vincefort.bsky.social to talk about everything #BayesianDeepLearning! Thanks for the intro @marvinschmitt.com 🙏

New episode is out! How to build a winning Research group in a pro sports team, with Matthew Penn ⚽

One of the most original topics we talked about on the show! Make sure to tune in for some exotic destinations, original research and causal inference topics ;)

⚾ @fonnesbeck.bsky.social (@pymc-labs.bsky.social, @pymc.io) will be at the Field of Play Conference giving a talk on Bayesian modelling in baseball. 😎 Our host, @alex-andorra.bsky.social , will also be attending, don’t miss this chance to connect and chat research! 🔗 www.fieldofplay.co.uk

🎙 In this episode on @learnbayesstats.bsky.social , @fonnesbeck.bsky.social & @alex-andorra.bsky.social break it all down: ✅ Use Bayesian methods to 𝐪𝐮𝐚𝐧𝐭𝐢𝐟𝐲 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 ✅ Separate signal from noise with 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬 & 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐚𝐥 𝐭𝐢𝐦𝐞 𝐬𝐞𝐫𝐢𝐞𝐬 ✅ Future of @pymc.io and more!🤯 👇Listen here