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 371–380 of 2226 papers

TitleStatusHype
Bayesian Federated Model Compression for Communication and Computation Efficiency—0
Interactive Learning of Physical Object Properties Through Robot Manipulation and Database of Object MeasurementsCode0
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks—0
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear RegressionCode0
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation—0
Accounting for contact network uncertainty in epidemic inferences—0
Divide, Conquer, Combine Bayesian Decision Tree Sampling—0
A Unified Kernel for Neural Network Learning—0
Bridging the Sim-to-Real Gap with Bayesian Inference—0
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Benchmark Results

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