Top Tweets for #bayesianML
Great visit with the @bayesgroup in Bremen! π So many inspiring discussions on dynamic systems & probabilistic methods. Huge thanks to Dmitry Vetrov & the whole team for the warm welcome. Excited for future collaborations!
#Collaboration #Innovation #BayesianML

π― New Contextual Multi-Armed Bandits example in RxInferExamples.jl!
Fresh take using message passing inference.
No MCMC, no hyperparameters - just principled decision making.
https://t.co/DhH1MrL6Wx
#BayesianML #JuliaLang #RxInfer

Triggered by some recent papers, Nick and I wrote about Deep Ensembles, Bayes ensembles, and PAC-Bayesian ensembling:
https://t.co/m1AzX3qq5R
Let us know what you think.
#deeplearning #PACBayes #BayesianML #ML
π€Uncertainty in image retrieval? π§Frederik Warburg et al. got you covered with their new paper on Bayesian Metric Learning! π€Check it out: https://t.co/XSXEK363QB #ImageRetrieval #BayesianML #ML
From my experience, applied ML researchers should also get as deep as possible into the math of it. A single insight from math can save a day of experiments that arrive at the same conclusion with lesser confidence. #BayesianML
Amazing learnings in Prof. @nipun_batra's talk on #bayesianML. It was a pleasant experience to attend in-person talks in such cool settings.
Both online and offline students are ready for the afternoon session on Bayesian #MachineLearning by Prof. @nipun_batra.

RT @AleksanderMolak: π The second part of #Medium series on modeling uncertainty in neural networks using @TensorFlow #Probability is out now!
πΒ Published by @TDataScience
#bayesianML #machinelearning #python #TensorFlow #decision_science #uncerta⦠https://t.co/h2cFnB8vpM
Modeling uncertainty in neural networks with TensorFlow Probability by @AleksanderMolak https://t.co/CN3SWN9A6B
My first Arxiv submission on empirical study of applying Bayesian GLM for Bankruptcy prediction with expert in the loop https://t.co/uBi319LFxW #bayesianml :) #rstanarm @mcmc_stan
Fast Bayesian estimation of spatial count data models https://t.co/3WPJAZ3vml
The proposed variation inference approach is around 45 to 50 times faster than MCMC on a regular eight-core processor.
#statistics #bayesianML #variationalinference #approximateinference
Excited to learn more about Bayesian ML and Gaussian Processes today at the Oxford Machine Learning Summer School!
#OxML2020 #MachineLearning #data #DataScientist #phdlife #AI #DataScience #BayesianML #BigData #summerschool

@OilGains thanks for your suggestion!! yeah, probably π.. As explained in my PhD thesis, Bayes is consistent with Axiom of Probability. Hence Bayes is Probability! But we also need algorithms in Machine learning to compute it. So the tag #BayesianML seems valid.
https://t.co/d0JwGlkK54
Maximum posterior probability (MAP) acts like regularization for Maximum Likelihood probability #BayesianML
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