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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 1001–1010 of 2226 papers

TitleStatusHype
Efficient posterior inference & generalization in physics-based Bayesian inference with conditional GANs—0
Bayesian Inference in Physics-Based Nonlinear Flame Models—0
An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System—0
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue—0
Godot is not coming: when we will let innovations enter psychiatry?—0
Probing as Quantifying Inductive BiasCode0
A Bayesian Approach for Medical Inquiry and Disease Inference in Automated Differential DiagnosisCode0
On out-of-distribution detection with Bayesian neural networksCode0
Unsupervised Source Separation via Bayesian Inference in the Latent DomainCode1
Deep Bayesian inference for seismic imaging with tasksCode0
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Benchmark Results

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