SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1581–1590 of 2226 papers

TitleStatusHype
Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data—0
Deep Active Inference as Variational Policy GradientsCode0
Thompson Sampling on Symmetric α-Stable Bandits—0
Variational Inference MPC for Bayesian Model-based Reinforcement Learning—0
Learning in Volatile Environments with the Bayes Factor Surprise—0
Probabilistic CCA with Implicit Distributions—0
Adaptive particle-based approximations of the Gibbs posterior for inverse problems—0
Bandit Learning for Diversified Interactive Recommendation—0
Teaching deep neural networks to localize single molecules for super-resolution microscopyCode0
Parameter Estimation and Uncertainty Quantification for Systems Biology Models—0
Show:102550
← PrevPage 159 of 223Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified