Some really interesting insights about #Bayes & #LLMs in this new episode -- hope you'll enjoy!

Pierre-Simon Laplace@learnbayesstats.bsky.social · 3w ago

Bayesian methods aren't going away in the age of LLMs. Christopher Krapu joins @alex-andorra.bsky.social to discuss GPUs, Gaussian Processes, probabilistic AI and more! 🎧 learnbayesstats.com/episode/baye... #bayesian #GPU #AI #LLM #Gaussianprocess #probablisticai

Episode 161 of the show is out, with @lacerbi.bsky.social ! We dive into all things neural processes, fast #Bayesian inferences, and LLMs -- hope you enjoy 🖖

Pierre-Simon Laplace@learnbayesstats.bsky.social · last mo.

Episode 161 is out 🎧 In which @lacerbi.bsky.social explains why transformers are secretly neural processes, how his Amortized Conditioning Engine unifies inference and prediction, and why "amortize everything" needed a rethink. 🔗 learnbayesstats.com/episode/161-... #bayesian #bayesianinference

Such a blast to come on the show @vadenmasrani.bsky.social @incrementspod.bsky.social ! Always fun to nerd out on #Bayesian topics to start a day :)

Increments Podcast@incrementspod.bsky.social · last mo.

New ep! The haters of Bayesian epistemology @vadenmasrani.bsky.social and Benny spend some time defending Bayesian statistics alongside the Stats God @alex-andorra.bsky.social. The Reverend is finally getting his comeuppance on Increments www.youtube.com/watch?v=7BZV...

🎙️ New episode! @alex-andorra.bsky.social sits down with Matthijs Hollanders on Bayesian occupancy models for wildlife data - what they are, why camera traps break classical approaches, and how his occARU R package handles it with hierarchical GPs and shrinkage priors. 🔗 lnkd.in/dw3WuMBg #bayes

Check out the new baygent skill @alex-andorra.bsky.social and I wrote to automate your amortized workflows! 🚀 learnbayesstats.com/blog-posts/a...

Train Once, Infer a Million Times: Bayesian Inference That's (Finally) Cheap at Query Time

MCMC re-runs from scratch on every new dataset. Amortized Bayesian inference pays the cost once -- then gives you a posterior in milliseconds, forever. Stefan Radev (BayesFlow creator) and I built an ...

learnbayesstats.com

Getting back to the basics with this one! What even *is* #BayesianStats ?? Prepare to get your mind blown by Vaden Masrani...

Pierre-Simon Laplace@learnbayesstats.bsky.social · 2mo ago

🎙️ Bayesian epistemology is Bayesian statistics minus the statistics. In ep 160 Vaden Masrani joins @alex-andorra.bsky.social to talk about why Bayes' theorem is great with real data, why it breaks down on one-off future events with nothing to count👇 🔗 lnkd.in/d3v42BU2 #bayesianstatistics

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...

GitHub - Learning-Bayesian-Statistics/baygent-skills: A set of skills to call your agent Bayes. Thomas Bayes.

A set of skills to call your agent Bayes. Thomas Bayes. - Learning-Bayesian-Statistics/baygent-skills

github.com

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!

Pierre-Simon Laplace@learnbayesstats.bsky.social · 3mo ago

Episode 158 is out 🎙️ @alex-andorra.bsky.social sits down with Stefan Radev to talk amortized Bayesian inference, multiverse analysis, and what a foundation model for Bayesian inference should actually look like and more.. 🔗 lnkd.in/dau9_eA7 #BayesianStatistics #AmortizedInference #MachineLearning

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 😉

Pierre-Simon Laplace@learnbayesstats.bsky.social · 4mo ago

🎙️ New episode alert! In this episode @alex-andorra.bsky.social & 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 ... lnkd.in/dCY85k4g

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

Pierre-Simon Laplace@learnbayesstats.bsky.social · 4mo ago

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.bsky.social and Adam Foster covers: 👉Expected information gain 👉BALD 👉Deep adaptive design and more ... 🎧 lnkd.in/ebjV9xXS

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!

Pierre-Simon Laplace@learnbayesstats.bsky.social · 5mo ago

🎙️ New episode of Learning Bayesian Statistics! EP 155 with @alex-andorra.bsky.social & Andreas Munk, why Bayesian inference still hasn't broken into everyday use. The barrier isn't the math, it's the mental shift 🔗 lnkd.in/gchb6bqj #Bayesian #ProbablisticProgramming

⚽ 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...

I Built an Agent That Refuses to Say "Causes"

Coding agents confidently say "X causes Y" without drawing a DAG, checking assumptions, or running refutation tests. I built an Agent Skill that won't let them. 100% eval pass rate vs 68% without -- t...

learnbayesstats.com

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...

baygent-skills/causal-inference at main · Learning-Bayesian-Statistics/baygent-skills

A set of skills to call your agent Bayes. Thomas Bayes. - Learning-Bayesian-Statistics/baygent-skills

github.com

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

Pierre-Simon Laplace@learnbayesstats.bsky.social · 5mo ago

New Episode Alert! 🎙️ Scaling #BayesianCausalInference with Thomas Pinder, Netflix & creator of GPJax Essential listening for anyone working at the frontier of Bayes, Experimentation & Causal Inference 📈 🔗 learnbayesstats.com/episode/154-... #Bayesian #JAX #MachineLearning #CausalInference #GPJax

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

Alexandre Andorra@alex-andorra.bsky.social · 5mo ago

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...

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...

A Researcher Stress-Tested My Bayesian Agent Skill. Here's What Broke

A researcher stress-tested my Bayesian Agent Skill on a real hierarchical model. It caught the workflow violations but missed a subtle prediction bug, had no sparsity priors, and lacked classification...

learnbayesstats.com

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...

I Taught My Coding Agent to Think Like a Bayesian

Teach your AI coding agent to think like a Bayesian. Discover the bayesian-workflow Agent Skill that prevents subtle statistical errors in PyMC models.

learnbayesstats.com

New episode is out 🍾

Pierre-Simon Laplace@learnbayesstats.bsky.social · 5mo ago

Fundraising = Belief Updating? 🧠📉 New episode is out! I'm talking with Cherian Koshy about the Neuroscience of Philanthropy. We discuss: ✅ Why generosity is hardwired ✅ Solving the Generosity Gap ✅ Cognitive friction ✅ Ethical AI Check it out: 🔗 learnbayesstats.com/episode/neur...

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.

Alexandre Andorra@alex-andorra.bsky.social · 6mo ago

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!

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...

GitHub - Learning-Bayesian-Statistics/baygent-skills: A set of skills to call your agent Bayes. Thomas Bayes.

A set of skills to call your agent Bayes. Thomas Bayes. - Learning-Bayesian-Statistics/baygent-skills

github.com

Pierre-Simon Laplace@learnbayesstats.bsky.social · 6mo ago

Hellooooooo my dear Bayesians! We just open-sourced an #AgentSkill that teaches coding agents to do #Bayesian stats properly. No more skipped diagnostics, no more point estimates without uncertainty, no more "trace plots look fine". Works with Claude Code, Cursor, Kimi, Gemini CLI, and more

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!

Pierre-Simon Laplace@learnbayesstats.bsky.social · 6mo ago

Episode 152 is out 🎙️ Host @alex-andorra.bsky.social talks with Daniel Saunders about a Bayesian decision theory workflow. Big idea: stop optimizing for model accuracy and start optimizing for decision value. 🔗 lnkd.in/gw_uGaZc #Bayesian #DecisionTheory #DataScience #Optimization

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...

Diffusion Models in Simulation-Based Inference: A Tutorial Review

Diffusion models have recently emerged as powerful learners for simulation-based inference (SBI), enabling fast and accurate estimation of latent parameters from simulated and real data. Their score-b...

arxiv.org

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

You Can Just Make Stuff with OpenCode and Claude Opus 4.5

written by Eric J. Ma on 2025-12-28 | tags: ai opencode claude automation workflow llm reasoning development review tools

buff.ly

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 🖖

Pierre-Simon Laplace@learnbayesstats.bsky.social · 8mo ago

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. 🔗 learnbayesstats.com/episode/148-... #newEpisode #bayes

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

Pierre-Simon Laplace@learnbayesstats.bsky.social · 8mo ago

Fast Bayesian inference is great… until you’re babysitting convergence. @alex-andorra.bsky.social 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 🎧 lnkd.in/gAX2iaHz #bayesianinference

🎙️ 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!

Pierre-Simon Laplace@learnbayesstats.bsky.social · 9mo ago

🎙️ What does it take to grow in tech? Jordan Thibodeau shares lessons from years inside top tech cultures with @alex-andorra.bsky.social ✅ Bayesian thinking as a practical advantage ✅ AI amplifies skill, not replaces it ✅ Networking & sharing knowledge matter 🎧 lnkd.in/ghk6D6nH #bayes #career

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!

Pierre-Simon Laplace@learnbayesstats.bsky.social · 10mo ago

Bayesian deep learning helps ML models understand their uncertainty In this episode @alex-andorra.bsky.social talks with Maurizio Filippone about Gaussian Processes, scalable inference, MCMC, and Bayesian deep learning at scale 🎧 learnbayesstats.com/episode/144-... #BayesianStats #AI #ML #Bayes