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 1651–1660 of 2226 papers

TitleStatusHype
A prediction rigidity formalism for low-cost uncertainties in trained neural networks—0
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling—0
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology—0
A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method—0
A Probabilistic Model for Canonicalizing Named Entity Mentions—0
A Probabilistic Model of Social Decision Making based on Reward Maximization—0
A Probabilistic Semi-Supervised Approach with Triplet Markov Chains—0
A rational decision making framework for inhibitory control—0
A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading—0
A Relaxed Drift Diffusion Model for Phylogenetic Trait Evolution—0
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Benchmark Results

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