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 781–790 of 2226 papers

TitleStatusHype
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition—0
Bayesian Inference with Posterior Regularization and applications to Infinite Latent SVMs—0
A Probabilistic Semi-Supervised Approach with Triplet Markov Chains—0
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning—0
A Probabilistic Model of Social Decision Making based on Reward Maximization—0
Bayesian Inference with Generative Adversarial Network Priors—0
Bayesian inference with finitely wide neural networks—0
A Probabilistic Model for Canonicalizing Named Entity Mentions—0
A Formal Calculus for International Relations Computation and Evaluation—0
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics—0
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Benchmark Results

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