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 1261–1270 of 2226 papers

TitleStatusHype
Bridging Privacy and Robustness for Trustworthy Machine Learning—0
Decipherment Complexity in 1:1 Substitution Ciphers—0
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control—0
Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
Declarative Modeling and Bayesian Inference of Dark Matter Halos—0
Decoupled Variational Gaussian Inference—0
Deep Active Inference for Autonomous Robot Navigation—0
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference—0
Deep de Finetti: Recovering Topic Distributions from Large Language Models—0
Deep Ensemble as a Gaussian Process Approximate Posterior—0
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Benchmark Results

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