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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 1011–1020 of 2226 papers

TitleStatusHype
Generative models and Bayesian inversion using Laplace approximation—0
Variational inference of fractional Brownian motion with linear computational complexity—0
Quantifying active and resistive stresses in adherent cells—0
Flexible Amortized Variational Inference in qBOLD MRICode0
Bayesian inference via sparse Hamiltonian flowsCode0
Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data—0
Sampling Bias Correction for Supervised Machine Learning: A Bayesian Inference Approach with Practical Applications—0
Online Dynamic Parameter Estimation of an Alkaline Electrolysis System Based on Bayesian Inference—0
Variational methods for simulation-based inferenceCode0
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian InferenceCode0
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Benchmark Results

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