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 531–540 of 2226 papers

TitleStatusHype
A Multi-armed Bandit MCMC, with applications in sampling from doubly intractable posterior—0
A Bayesian Approach to Multimodal Visual Dictionary Learning—0
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection—0
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs—0
A Bayesian Approach to Identifying Representational Errors—0
Active recursive Bayesian inference using Rényi information measures—0
Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems—0
BayesAdapter: enhanced uncertainty estimation in CLIP few-shot adaptation—0
Exchangeable Sequence Models Quantify Uncertainty Over Latent Concepts—0
BAT.jl -- A Julia-based tool for Bayesian inference—0
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Benchmark Results

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