OSC hosts 8 public lectures, open for everyone & free of charge: Sept. 07 - 11, 2026 Each lecture offers valuable insights for students, researchers, & anyone ready to embrace open science practices. Get an overview here: bit.ly/4yz6dHP 📅 Registration for online attendance is open: bit.ly/4pI2GTC

ArviZ now has built-in tools for prior & likelihood sensitivity analysis via power-scaling! Instead of fitting multiple models with different priors, you fit once and use importance sampling to approximate the effect of perturbing the prior or likelihood.

@aloctavodia.bsky.social has been porting Bayesian Workflow book avehtari.github.io/Bayesian-Wor... case studies to Python using CmdStanPy, numpyro, ArviZ, Bambi, and kulprit arviz-devs.github.io/bayesian-wor... He is working on porting the rest of the case studies, too

Bayesian Workflow book: Case studies in Python – Bayesian Workflow case studies in Python

arviz-devs.github.io

openRxiv has arrived! We’re thrilled to announce the launch of openRxiv as an independent, researcher-led nonprofit to oversee bioRxiv and medRxiv, the world’s leading preprint servers for life and health sciences. openrxiv.org/introducing-... #openRxiv #OpenScience #Preprints #bioRxiv #medRxiv

Osvaldo is translating the Bayesian Workflow book's case studies to Python, very useful in case you are snake person arviz-devs.github.io/bayesian-wor...

Osvaldo Martin@aloctavodia.bsky.social · 3w ago

Look what was waiting on my desk this morning! It's so great to finally see #BayesianWorkflow in print.

2/ Amortized inference is so fast that it runs interactively in your browser! Play around with our methods here: acerbilab.github.io/nanoACE/ These are small models so you can have fun pushing them to the limit - sometimes we learn by building things, more often than not by breaking them... :)

📘 With the release of our textbook "Bayesian Workflow" (avehtari.github.io/Bayesian-Wor...), I figured I'd also share the content of my graduate course on the topic at UBC. 🌎 charlesm93.github.io/stat547/ The course contains overlapping and complementary material, homeworks and reading.

Bayesian Workflow book: Website – Bayesian Workflow book

Website for the Bayesian Workflow book by Gelman, Vehtari, McElreath, et al. — case studies, code, and exercises in R and Stan.

avehtari.github.io

All three books I've co-authored are freely available online for non-commercial use: - #Bayesian Data Analysis, 3rd ed (aka BDA3) at stat.columbia.edu/~gelman/book/ - #Regression and Other Stories at avehtari.github.io/ROS-Examples/ - Active Statistics at avehtari.github.io/ActiveStatis...

tl;dr Model selection is not a substitute for building good models in the first place

New paper "To select or not to select: predictively consistent priors instead of model selection" with Anna Elisabeth Riha, Leevi Lindgren, @davidkohns.bsky.social, @paulbuerkner.com arxiv.org/abs/2606.22850 Model selection is not a substitute for building good models in the first place 1/

The radar plot is the most popular chart in football analytics. It might also be the least effective. Chris Fonnesbeck breaks down why and builds the replacement: dub.sh/BUsCcev #SportsAnalytics #DataViz #Bayesian

We're open-sourcing pathmc! Structural causal models + #Bayesian estimation in one package. Define assumptions once, then estimate effects, test identifiability, run interventions, and perform sensitivity analysis. Docs: dub.sh/T0ASJt2 GitHub: dub.sh/rqiDyfg

Have you seen MATILDA (matilda.fss.uu.nl)? Which stands for Measurement, Analysis & Theory for Intensive Longitudinal Data. MATILDA is a website with educational articles that help researchers align theory, measurement, and analysis when studying processes using intensive longitudinal data.

Almost 5 years in the making... "Hyperparameter Optimization in Machine Learning" is finally out! 📘 We designed this monograph to be self-contained, covering: Grid, Random & Quasi-random search, Bayesian & Multi-fidelity optimization, Gradient-based methods, Meta-learning. arxiv.org/abs/2410.22854

AI agents finally have a proper CLI for Jupyter notebooks. nb-cli lets agents read, write, execute, and search notebooks without a running server, built in Rust, optimized for LLM context windows. Read the blog: blog.jupyter.org/nb-cli-a-com...

nb-cli: A Command-Line Interface for AI Agents and Notebook Automation

The rise of AI coding agents has transformed how we think about developer tools. Large language models like Claude, GPT, and others are…

blog.jupyter.org

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

CERN to host Europe’s flagship open access publishing platform Find out more: home.cern/news/news/ce...