SOTAVerified

Bayesian Inference

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

Papers

Showing 18311840 of 2226 papers

TitleStatusHype
Efficient Bayesian Inference of Sigmoidal Gaussian Cox ProcessesCode0
Adversarial α-divergence Minimization for Bayesian Approximate InferenceCode0
Quantile Propagation for Wasserstein-Approximate Gaussian ProcessesCode0
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior InferenceCode0
Stein Point Markov Chain Monte CarloCode0
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in NeuroimagingCode0
Efficient identification of informative features in simulation-based inferenceCode0
Variationally Inferred Sampling Through a Refined Bound for Probabilistic ProgramsCode0
matLeap: A fast adaptive Matlab-ready tau-leaping implementation suitable for Bayesian inferenceCode0
Spike Sorting using the Neural Clustering ProcessCode0
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Benchmark Results

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