Tradeoff between approximate algorithms and MCMC in Bayesian computation via Bayesian Workflow: arxiv.org/abs/2011.01808

Model-based Inference for Causal Effects in Completely Randomized Experiments by Joon-Ho Lee et al. mc-stan.org/users/document…

Probability does not promote play (games of chance): from Abraham de Moivre to Lord Carpenter in the preface to the Doctrine of Changes.

"On Bayesian Workflow" talk by Aki Vehtari - @[email protected] youtu.be/ppKpwtGy8KQ

(Bayesian) Survival Models & Biostatistics for Cancer Research, withJacqueline Buros (jackiburos) via Alexandre Andorra and his Learn Bayes Stats podcast learnbayesstats.com/episode/39-sur…

The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions by Raj Agrawal et al. arxiv.org/abs/1905.06501 github.com/pyro-ppl/pyro/… youtube.com/watch?v=Xnxnoq…

"Pathfinder: Parallel quasi-Newton variational inference" by Lu Zhang, Bob Carpenter, Andrew Gelman, and Aki Vehtari arxiv.org/abs/2108.03782

Towards responsible patient-level causal inference: taking uncertainty seriously by Uri Shalit youtu.be/nd1a97f93OE

Stan developer Rok Češnovar is stopping by at 12 PM ET to talk to us about the current state of Stan how we got here, and where we are going. Join us on the Calibrated Webcast. hopin.com/events/the-cur…

Introduction to Nonparametric Bayes by Arman Oganisian (Arman Oganisian) youtu.be/Sv4sAjZjcBg

Stan developer Rok Češnovar talks about the current state of Stan how we got here, and where we are going. youtu.be/EJLXoDBoVko

Bayesian Modeling and Computation in Python by aloctavodia.bsky.social, RavinKumar, and @junpenglao is now available online: bayesiancomputationbook.com

Lizzie Wolkovivh: Predicting future forest tree communities and winegrowing regions with Stan youtu.be/gKWedtPjyQE

Regression and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari is now available online. avehtari.github.io/ROS-Examples/ users.aalto.fi/~ave/ROS.pdf

Solving Wordle using information theory by Grant Sanderson youtu.be/v68zYyaEmEA

Tuning-Free Generalized Hamiltonian Monte Carlo by Matt Hoffman and Pavel Sountsov. proceedings.mlr.press/v151/hoffman22…

Bayes Rules! An Introduction to Applied Bayesian Modeling by Alicia A. Johnson, Miles Q. Ott, Mine Dogucu is available online: bayesrulesbook.com

"Past, Present, and Future of Software for Bayesian Inference" is a paper by Erik Štrumbelj and colleagues. It's a nice overview and contains data on the number of downloads of Bayes-related packages in Python and R. stat.columbia.edu/~gelman/resear…

New Book: Bayesian Statistical Modeling with Stan, R, and Python by Kentaro Matsuura. Here is a review: statmodeling.stat.columbia.edu/2023/11/27/boo…

causalBETA: An R Package for Bayesian Semiparametric Causal Inference with Event-Time Outcomes by Han Ji and Arman Oganisian arxiv.org/abs/2310.12358 github.com/RuBBiT-hj/caus…