at my job Iโm 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 ๐
See you soon in the Intuitive Bayes' Discourse ๐
topmate.io/alex_andorra...
Looks awesome @ericmjl.bsky.social ! What's your favorite AI workflow and setup to write on these projects?
I don't code anymoreโI 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 ฬถrฬถiฬถgฬถhฬถtฬถ Bayesian way, with no other than Scott Berry, from Berry Consultants, LLC!
Enjoy, and happy new year, my dear Bayesians ๐
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
๐๏ธ How do you tackle extreme physics experiments? Ethan Smith shares insights with @alex-andorra.bsky.social
โ
Bayesian inference for sparse, noisy data
โ
Priors guide well-established physical models
โ
Scaling Bayesian workflows across teams
๐ง 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 :(
๐ฝ๏ธ 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
๐ง learnbayesstats.com/episode/143-...
#bayes #nutrition
How to run #BART and #TreeModels fast in #Python -- new episode is out, with @gstechschulte.bsky.social !
๐ NFL meets Bayesian stats!
In this episode @alex-andorra.bsky.social chats with Ron Yurko on
๐ Writing your own models
๐ Building a sports analytics portfolio
๐ Pitfalls of modelling expectations
๐ Using tracking data for player insights
๐ Causal thinking in football data
๐ง 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
๐จ MCMC or INLA?
๐คฏ MCMC = slow sampling.
โก INLA = fast, smart approximations. No chains, no waiting.
๐๏ธ On LBS, @alex-andorra.bsky.social talks with Haavard Rue & Janet Van Niekerk about how INLA works, when to use it, and why itโs a game-changer.
๐ง 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 ๐ฒ๐
๐ฐ๐ฒ๐น๐น๐ฒ๐ป๐ ๐ฒ๐
๐ฎ๐บ๐ฝ๐น๐ฒ using the ๐๐ผ๐ฟ๐๐ฒ๐๐ต๐ผ๐ฒ ๐ฃ๐ฟ๐ถ๐ผ๐ฟ โ a powerful Bayesian tool for #SparseRegression โ 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 ๐
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 ๐
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 ๐พ
Come say hi on June 24 at Imperial College London! We'll be talking about uncertainty quantification.
๐๏ธ www.eventbrite.co.uk/e/machine-le...
๐ฒ Bayesian Nerds Assemble! ๐ฒ
Live panel on "Machine Learning & Uncertainty" at Imperial College London, June 24. I'm hosting, joined by Mรฉlodie 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:
๐ท #DynamicRegression
๐ท #StateSpaceModels
๐ท Predictively consistent priors
๐ท Bayesian Rยฒ
๐ท 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 ๐จ
