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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 111–120 of 2226 papers

TitleStatusHype
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian InferenceCode1
Gaussian process learning of nonlinear dynamicsCode1
Antipodes of Label Differential Privacy: PATE and ALIBICode1
Inferring COVID-19 spreading rates and potential change points for case number forecastsCode1
Laplacian Autoencoders for Learning Stochastic RepresentationsCode1
Learning by example: fast reliability-aware seismic imaging with normalizing flowsCode1
Learning to Generalize across Domains on Single Test SamplesCode1
Lifelong Incremental Reinforcement Learning with Online Bayesian InferenceCode1
Memory-Based Meta-Learning on Non-Stationary DistributionsCode1
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
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Benchmark Results

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