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 1221–1230 of 2226 papers

TitleStatusHype
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling—0
Bayesian Numerical Methods for Nonlinear Partial Differential Equations—0
Robust Generalised Bayesian Inference for Intractable LikelihoodsCode0
When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution—0
Measuring diachronic sense change: new models and Monte Carlo methods for Bayesian inferenceCode0
The computational asymptotics of Gaussian variational inference and the Laplace approximationCode0
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
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Benchmark Results

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