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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 131–140 of 2226 papers

TitleStatusHype
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksCode1
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy imagesCode1
Calibrating Transformers via Sparse Gaussian ProcessesCode1
Bayesian neural networks via MCMC: a Python-based tutorialCode1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
Conditional score-based diffusion models for Bayesian inference in infinite dimensionsCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
Bayesian Uncertainty for Gradient Aggregation in Multi-Task LearningCode1
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Benchmark Results

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