Alexandre Andorra

New episode is out 🍾

Thanks @minedogucu.com ! Sounds like @oaggimenez.bsky.social should come on @learnbayesstats.bsky.social ... Ca te dit Olivier?

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 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...

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...

Looks awesome @ericmjl.bsky.social ! What's your favorite AI workflow and setup to write on these projects?

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

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!

Nope Stephen :(

🍽️ 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 🙏

A Beginner's Guide to State Space Modeling - PyData Berlin 2025 **State Space Models** (SSMs) are powerful tools for time series analysis, widely used in finance, economics, ecology, and engineering. They allow researchers t... By Alexandre Andorra, Jesse Grabowsk...

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...

Machine Learning & Uncertainty: Shaping the Next Decade Statistical machine learning is powering groundbreaking advances, yet uncertainty quantification remains one of its biggest challenges.

🎲 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...