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 651–660 of 2226 papers

TitleStatusHype
A majorization-minimization algorithm for nonnegative binary matrix factorization—0
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review—0
Combining human cell line transcriptome analysis and Bayesian inference to build trustworthy machine learning models for prediction of animal toxicity in drug development—0
Active pooling design in group testing based on Bayesian posterior prediction—0
Combining X-Vectors and Bayesian Batch Active Learning: Two-Stage Active Learning Pipeline for Speech Recognition—0
Communication-Efficient Distributed Statistical Inference—0
BAT.jl -- A Julia-based tool for Bayesian inference—0
Comparative Study of Inference Methods for Interpolative Decomposition—0
BI-EqNO: Generalized Approximate Bayesian Inference with an Equivariant Neural Operator Framework—0
Bidirectional Recurrent Neural Networks as Generative Models—0
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Benchmark Results

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