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 1561–1570 of 2226 papers

TitleStatusHype
Variationally Inferred Sampling Through a Refined Bound for Probabilistic ProgramsCode0
Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in GlaucomaCode0
Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing—0
Bayesian posterior repartitioning for nested samplingCode0
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control—0
Convergence Rates of Variational Inference in Sparse Deep Learning—0
Bayesian Inference for Large Scale Image Classification—0
Variational Bayes on ManifoldsCode0
Bayesian Incremental Inference Update by Re-using Calculations from Belief Space Planning: A New Paradigm—0
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement—0
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Benchmark Results

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