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 811–820 of 2226 papers

TitleStatusHype
Bayesian Neural Network Detector for an Orthogonal Time Frequency Space Modulation—0
Variational Bayesian inference for CP tensor completion with side information—0
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport—0
Cold Posteriors through PAC-Bayes—0
Multiband Delay Estimation for Localization Using a Two-Stage Global Estimation Scheme—0
Robust One Round Federated Learning with Predictive Space Bayesian InferenceCode0
Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk—0
Scaling multi-species occupancy models to large citizen science datasets—0
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift—0
Fidelity of Hyperbolic Space for Bayesian Phylogenetic InferenceCode0
Show:102550
← PrevPage 82 of 223Next →

Benchmark Results

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