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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 561–570 of 2226 papers

TitleStatusHype
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
Bridging Privacy and Robustness for Trustworthy Machine Learning—0
Clustered Mallows Model—0
Predictive, scalable and interpretable knowledge tracing on structured domainsCode0
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Benchmark Results

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