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 231–240 of 2226 papers

TitleStatusHype
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables—0
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology—0
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling—0
A theory of representation learning gives a deep generalisation of kernel methods—0
Augmented Message Passing Stein Variational Gradient Descent—0
A prediction rigidity formalism for low-cost uncertainties in trained neural networks—0
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks—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
Accelerating Multilevel Markov Chain Monte Carlo Using Machine Learning Models—0
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Benchmark Results

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