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 1601–1610 of 2226 papers

TitleStatusHype
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family ApproximationsCode0
Hierarchical Bayesian myocardial perfusion quantification—0
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial SettingsCode0
Sparse Bayesian Learning Approach for Discrete Signal Reconstruction—0
Generalizing Eye Tracking With Bayesian Adversarial Learning—0
Bayesian Hierarchical Dynamic Model for Human Action RecognitionCode0
Bayesian Inference Semantics: A Modelling System and A Test SuiteCode0
Greedy inference with structure-exploiting lazy mapsCode0
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
Cross-modal Variational Auto-encoder with Distributed Latent Spaces and Associators—0
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Benchmark Results

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