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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 1991–2000 of 2226 papers

TitleStatusHype
Bayesian Inference Semantics: A Modelling System and A Test SuiteCode0
A generative flow for conditional sampling via optimal transportCode0
Robust Generalised Bayesian Inference for Intractable LikelihoodsCode0
Being a Bit Frequentist Improves Bayesian Neural NetworksCode0
From Understanding the World to Intervening in It: A Unified Multi-Scale Framework for Embodied CognitionCode0
β-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of OutliersCode0
BClean: A Bayesian Data Cleaning SystemCode0
Full-waveform earthquake source inversion using simulation-based inferenceCode0
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in BadlandsCode0
Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal NeuronsCode0
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Benchmark Results

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