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 1241–1250 of 2226 papers

TitleStatusHype
Verbalized Probabilistic Graphical Modeling with Large Language Models—0
W2WNet: a two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality—0
Walsh-Hadamard Variational Inference for Bayesian Deep Learning—0
Wasserstein Measure Coresets—0
Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference—0
Wasserstein Variational Inference—0
WattScale: A Data-driven Approach for Energy Efficiency Analytics of Buildings at Scale—0
Weakly-supervised Localization of Manipulated Image Regions Using Multi-resolution Learned Features—0
Webservices for Bayesian Learning—0
Weighted Community Detection and Data Clustering Using Message Passing—0
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Benchmark Results

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