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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 681–690 of 2226 papers

TitleStatusHype
Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventionsCode0
Data-driven Approach for Interpolation of Sparse DataCode0
Bayesian Approaches to Shrinkage and Sparse EstimationCode0
MPC-guided Imitation Learning of Neural Network Policies for the Artificial PancreasCode0
A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net ModelsCode0
Multilevel neural simulation-based inferenceCode0
Consistent and fast inference in compartmental models of epidemics using Poisson Approximate LikelihoodsCode0
Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamicsCode0
Bayesian posterior repartitioning for nested samplingCode0
Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interactionCode0
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Benchmark Results

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