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 1001–1010 of 2226 papers

TitleStatusHype
Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC—0
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach—0
Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization—0
Flexible Bayesian Inference on Partially Observed Epidemics—0
Divide, Conquer, Combine Bayesian Decision Tree Sampling—0
Flexible Mixture Modeling on Constrained Spaces—0
Bayesian Inference for Gamma Models—0
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation—0
Forecasting Macroeconomic Dynamics using a Calibrated Data-Driven Agent-based Model—0
Distribution-Level AirComp for Wireless Federated Learning under Data Scarcity and Heterogeneity—0
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Benchmark Results

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