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 2161–2170 of 2226 papers

TitleStatusHype
Bayesian Differential Privacy through Posterior Sampling—0
Fast Dual Variational Inference for Non-Conjugate LGMs—0
Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks—0
Declarative Modeling and Bayesian Inference of Dark Matter Halos—0
NLI Shared Task 2013: MQ Submission—0
A Bayesian Approach to Multimodal Visual Dictionary Learning—0
Mean field variational Bayesian inference for support vector machine classification—0
Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation—0
Towards an Author-Topic-Term-Model Visualization of 100 Years of German Sociological Society Proceedings—0
Inferring ground truth from multi-annotator ordinal data: a probabilistic approach—0
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Benchmark Results

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