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 1871–1880 of 2226 papers

TitleStatusHype
Bayesian posterior approximation via greedy particle optimization—0
Bayesian Posterior Perturbation Analysis with Integral Probability Metrics—0
Bayesian Prediction-Powered Inference—0
Bayesian Predictive Coding—0
Bayesian Probabilistic Matrix Factorization—0
Bayesian Reasoning with Trained Neural Networks—0
Bayesian reconstruction of HIV transmission trees from viral sequences and uncertain infection times—0
Bayesian Reinforcement Learning: A Survey—0
Bayesian sense of time in biological and artificial brains—0
Bayesian Sensing for Time-Varying Channels in ISAC Systems—0
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Benchmark Results

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