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 1141–1150 of 2226 papers

TitleStatusHype
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution—0
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
The computational asymptotics of Gaussian variational inference and the Laplace approximationCode0
Learning by example: fast reliability-aware seismic imaging with normalizing flowsCode1
Revisiting Bayesian Autoencoders with MCMCCode0
COVID-19 detection using chest X-rays: is lung segmentation important for generalization?Code0
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC—0
Generalizing to the Open World: Deep Visual Odometry with Online Adaptation—0
A Bayesian Approach to Identifying Representational Errors—0
W2WNet: a two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality—0
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Benchmark Results

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