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Bayesian Inference

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

Papers

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Showing 1181–1190 of 2226 papers

TitleStatusHype
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance—0
Robust Bayesian Inference for Berkson and Classical Measurement Error Models—0
Robust Bayesian Nonnegative Matrix Factorization with Implicit Regularizers—0
SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations—0
Bayesian data-driven discovery of partial differential equations with variable coefficients—0
Robust Energy Storage Scheduling for Imbalance Reduction of Strategically Formed Energy Balancing Groups—0
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications—0
Robust Gaussian Process Regression with Huber Likelihood—0
Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks—0
Roll-back Hamiltonian Monte Carlo—0
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Benchmark Results

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