I just published "Stan Algorithms: Where to Start?" @mcmc_stan https://t.co/2Ui3kuBP1Q
— Daniel Lee (@djsyclik) January 19, 2022
I just published "Stan Algorithms: Where to Start?" @mcmc_stan https://t.co/2Ui3kuBP1Q
— Daniel Lee (@djsyclik) January 19, 2022
Bayesian hierarchical stacking: Some models are (somewhere) useful https://t.co/FCyazmxOy0
— Andrew Gelman et al. (@StatModeling) August 11, 2021
Despite its popularity in the covariate shift setting, Bayesian model averaging can surprisingly hurt OOD generalization! https://t.co/AqbH4f29FG 1/5 https://t.co/OawZs6AV7n pic.twitter.com/SiPHp8mQrm
— Andrew Gordon Wilson (@andrewgwils) June 23, 2021
The Bayesian modeling equivalent is this @StatModeling @avehtari @dan_p_simpson et al. Bayesian workflow paper: https://t.co/aJSMVxCvA1
— Sean J. Taylor (@seanjtaylor) April 13, 2021
Having strict process to ensure good results is so important, no matter how much experience you have. Very easy to go off the rails otherwise.
⚠️ SO YOU WANT TO BE A BAYESIAN⚠️ :
— Chelsea Parlett-Pelleriti (@ChelseaParlett) November 20, 2020
(since I compiled a quick list of Bayesian resources today, I figured I should share; these are just my opinion!) https://t.co/9incv2VOfs
PyMC3 will use Theano (yes!) with a new JAX backend and PyMC4 based on TensorFlow will not be developed anymore: https://t.co/sNfwwUIUMz
— Denny Britz (@dennybritz) November 7, 2020
This is really cool. They replaced Theano's C-based ops with JAX. I hope Theano makes a comeback across other libraries too.
New R package rmsb: Bayesian counterpart to the rms (regression modeling strategies) package now on CRAN. Uses pre-compiled @mcmc_stan code. Information including lots of examples at https://t.co/XSMsQyqA1J #rmscourse @vandy_biostat @VUDataScience
— Frank Harrell (@f2harrell) August 5, 2020
A great primer on Bayesian Optimization: https://t.co/NJIG77N2Uq
— Martin Görner (@martin_gorner) July 17, 2020
Finally I know how AI Platform's hyperparameter tuning feature works. (https://t.co/A2jdwwSo5g)
Ever wondered what Bayesians are so excited about? Here's a walkthrough of a couple of mostly-correct examples for the newbie.https://t.co/LdMfV1l02U
— Brandon Rohrer (@_brohrer_) June 22, 2020
You say Normalizing Flows? We see Bayesian Networks! Quite excited to announce two papers @WehenkelAntoine and I have just released on arXiv! https://t.co/XnRPCOgC4G + https://t.co/6TpUItXKiF Thread below 👇 https://t.co/0dIVEDABJg
— Gilles Louppe (@glouppe) June 5, 2020
Excited to release rank-1 Bayesian neural nets, achieving new SOTA on uncertainty & robustness across ImageNet, CIFAR-10/100, and MIMIC. We do extensive ablations to disentangle BNN choices.@dusenberrymw @Ghassen_ML @JasperSnoek @kat_heller @balajiln et al https://t.co/aMfBvVkl0v pic.twitter.com/T5sQDkO0xR
— Dustin Tran (@dustinvtran) May 18, 2020
Exploring Bayesian Optimization — A new Distill article by @ApoorvAgnihotr2 and @nipun_batrahttps://t.co/xDvuSjPoFU
— Distill (@distillpub) May 5, 2020