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 261–270 of 2226 papers

TitleStatusHype
Approximate Inference with the Variational Holder Bound—0
Approximate Inference for Spectral Mixture Kernel—0
A Bayesian model for identifying hierarchically organised states in neural population activity—0
Approximate Gibbs Sampler for Efficient Inference of Hierarchical Bayesian Models for Grouped Count Data—0
Approximate Decentralized Bayesian Inference—0
Advancing Autonomous Vehicle Safety: A Combined Fault Tree Analysis and Bayesian Network Approach—0
BAR: Bayesian Activity Recognition using variational inference—0
BAT.jl -- A Julia-based tool for Bayesian inference—0
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models—0
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
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Benchmark Results

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