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 2191–2200 of 2226 papers

TitleStatusHype
Semantic Parsing with Bayesian Tree Transducers—0
A Probabilistic Model for Canonicalizing Named Entity Mentions—0
Estimating Compact Yet Rich Tree Insertion Grammars—0
Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation—0
Variational Bayesian Inference with Stochastic Search—0
Bayesian inference for logistic models using Polya-Gamma latent variablesCode1
Webservices for Bayesian Learning—0
Inference in continuous-time change-point models—0
Practical Variational Inference for Neural Networks—0
Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning—0
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Benchmark Results

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