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 1181–1190 of 2226 papers

TitleStatusHype
Unifying Bayesian Inference and Vector Space Models for Improved Decipherment—0
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift—0
Unrolled denoising networks provably learn optimal Bayesian inference—0
Unsupervised Spectral Learning of WCFG as Low-rank Matrix Completion—0
Unsupervised structured semantic inference for spoken dialog reservation tasks—0
Upper Bound of Real Log Canonical Threshold of Tensor Decomposition and its Application to Bayesian Inference—0
Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation—0
V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures—0
Value of Information Analysis via Active Learning and Knowledge Sharing in Error-Controlled Adaptive Kriging—0
Value of Information and Reward Specification in Active Inference and POMDPs—0
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Benchmark Results

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