SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Showing 16011610 of 2226 papers

TitleStatusHype
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting0
Accelerating Langevin Sampling with Birth-death0
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data AugmentationCode0
Estimating Risk and Uncertainty in Deep Reinforcement LearningCode0
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-RiskCode0
Exploring helical dynamos with machine learningCode0
Automatic Posterior Transformation for Likelihood-Free InferenceCode1
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations0
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference0
Variational approximations using Fisher divergence0
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Benchmark Results

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