SOTAVerified

Bayesian Inference

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

Papers

Showing 19811990 of 2226 papers

TitleStatusHype
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPsCode0
A Hamiltonian Monte Carlo Model for Imputation and Augmentation of Healthcare DataCode0
Stochastic gradient Markov chain Monte CarloCode0
Stochastic Gradient MCMC for Nonlinear State Space ModelsCode0
Near-Optimal Approximations for Bayesian Inference in Function SpaceCode0
Better Peer Grading through Bayesian InferenceCode0
Negative Binomial Process Count and Mixture ModelingCode0
Stochastic Gradient MCMC for State Space ModelsCode0
Network Plasticity as Bayesian InferenceCode0
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence ClusteringCode0
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Benchmark Results

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