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 1841–1850 of 2226 papers

TitleStatusHype
Flexible statistical inference for mechanistic models of neural dynamicsCode0
Spintronics based Stochastic Computing for Efficient Bayesian Inference System—0
Learning Asymmetric and Local Features in Multi-Dimensional Data through Wavelets with Recursive PartitioningCode0
Deep Neural Networks as Gaussian ProcessesCode0
Tensor Regression Meets Gaussian Processes—0
Grammar Induction for Minimalist Grammars using Variational Bayesian Inference : A Technical ReportCode0
Implicit Causal Models for Genome-wide Association Studies—0
Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection—0
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference—0
Bayesian Inference over the Stiefel Manifold via the Givens Representation—0
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Benchmark Results

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