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 1301–1310 of 2226 papers

TitleStatusHype
Generalized Posteriors in Approximate Bayesian ComputationCode0
Stein Variational Model Predictive Control—0
On a Variational Approximation based Empirical Likelihood ABC Method—0
Efficient and Transferable Adversarial Examples from Bayesian Neural NetworksCode0
Extending the statistical software package Engine for Likelihood-Free Inference—0
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation—0
Problems using deep generative models for probabilistic audio source separation—0
Differentially Private Bayesian Inference for Generalized Linear Models—0
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo—0
Micro-CT Synthesis and Inner Ear Super Resolution via Generative Adversarial Networks and Bayesian Inference—0
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Benchmark Results

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