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 1011–1020 of 2226 papers

TitleStatusHype
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation—0
Distribution-Level AirComp for Wireless Federated Learning under Data Scarcity and Heterogeneity—0
Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning—0
Formalizing Preference Utilitarianism in Physical World Models—0
Forming Real-World Human-Robot Cooperation for Tasks With General Goal—0
Bayesian inference for dynamic spatial quantile models with interactive effects—0
Foundation Models for Causal Inference via Prior-Data Fitted Networks—0
Free energy and inference in living systems—0
Free Energy Minimization: A Unified Framework for Modelling, Inference, Learning,and Optimization—0
Distribution learning via neural differential equations: minimal energy regularization and approximation theory—0
Show:102550
← PrevPage 102 of 223Next →

Benchmark Results

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