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

1/ Great chat with Alex Andorra aka @learnbayesstats.bsky.social about efficient inference, from amortized to surrogate-based approaches and a variety of related topics (prior-fitted networks, foundation models for inference and planning, etc.), many of which are neural processes in a trenchcoat.

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

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

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

Was so great chatting with you @learnbayesstats.bsky.social !!

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

🎙️ 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

🎙️ 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

🎙️ 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

So this is apparently happening

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

🚨 @rmcelreath.bsky.social @statmodeling.bsky.social & @avehtari.bsky.social are coming on the show mid-June to discuss their new book, Bayesian Workflow! ONE listener gets to bring a real Bayesian problem onto the recording and have the three of them work through it live. Here's how to enter 🧵

🚨 @rmcelreath.bsky.social @statmodeling.bsky.social & @avehtari.bsky.social are coming on the show mid-June to discuss their new book, Bayesian Workflow! ONE listener gets to bring a real Bayesian problem onto the recording and have the three of them work through it live. Here's how to enter 🧵

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

Bayesian Workflows, Foundation Models & Sensitivity

Stefan Radev explains how simulations improve Bayesian workflows, how to do cheap sensitivity and multiverse analysis, and where BayesFlow is headed next.

learnbayesstats.com

🎙️ 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

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 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 👇

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 · 4mo 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

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

Bayesian Causal Inference at Scale

Thomas Pinder discusses Bayesian causal inference and Gaussian processes. Explore synthetic control and diff-in-diff for industry

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...

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...

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 · 5mo 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

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...

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

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

🎙️ New episode out now - Episode 151: Diffusion Models in Python, a Live Demo In this episode, @alex-andorra.bsky.social 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 ... 🎧 lnkd.in/gMyAfrW5

Bayesian neural networks need one thing to matter: good uncertainty. Scaling them has always been the hard part In this episode, host @alex-andorra.bsky.social with Emmanuel Sommer, Jakob Robnik, & David Rügamer explain what’s changing, faster sampling, better dynamics & more .. 🎧 lnkd.in/g2W5cZQZ

Work in tech is changing fast, and not always in obvious ways. @alex-andorra.bsky.social 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. 🎧 lnkd.in/gcRJVT-s #FutureOfWork

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...

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

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

🎙️ 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

Now I'm also looking for a research software engineer to implement a pile of research results to R packages loo, posterior, bayesplot, projpred, priorsense, brms or/and Python packages ArviZ, Bambi and Kulprit. Apply by email with no specific deadline (see contact info at users.aalto.fi/~ave/)

Aki Vehtari@avehtari.bsky.social · 9mo ago

I'm now also looking for a postdoc with strong Bayesian background and interest in developing Bayesian cross-validation theory, methods and software. Apply by email with no specific deadline (see contact information at users.aalto.fi/~ave/). Others, please share