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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 1131–1140 of 2226 papers

TitleStatusHype
Consumer Demand Modeling During COVID-19 Pandemic—0
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlasCode1
Regularizing Explanations in Bayesian Convolutional Neural Networks—0
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical ImagingCode1
Invariant polynomials and machine learningCode0
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling—0
Bayesian Numerical Methods for Nonlinear Partial Differential Equations—0
Bayesian graph convolutional neural networks via tempered MCMCCode1
Robust Generalised Bayesian Inference for Intractable LikelihoodsCode0
Measuring diachronic sense change: new models and Monte Carlo methods for Bayesian inferenceCode0
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Benchmark Results

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