SOTAVerified

Bayesian Inference

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

Papers

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Showing 381–390 of 2226 papers

TitleStatusHype
Bridging Privacy and Robustness for Trustworthy Machine Learning—0
Predictive, scalable and interpretable knowledge tracing on structured domainsCode0
Clustered Mallows Model—0
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware PriorsCode0
Scalable Spatiotemporal Prediction with Bayesian Neural FieldsCode2
Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappingsCode0
In-context Exploration-Exploitation for Reinforcement Learning—0
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
Scalable Bayesian inference for the generalized linear mixed model—0
A prediction rigidity formalism for low-cost uncertainties in trained neural networks—0
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Benchmark Results

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