SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1561–1570 of 2226 papers

TitleStatusHype
Addressing Census data problems in race imputation via fully Bayesian Improved Surname Geocoding and name supplements—0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
A Deep Learning Approach to Dst Index Prediction—0
A deep learning framework for geodesics under spherical Wasserstein-Fisher-Rao metric and its application for weighted sample generation—0
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models—0
A Distributed Framework for the Construction of Transport Maps—0
Adjoint-aided inference of Gaussian process driven differential equations—0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
Advancing Autonomous Vehicle Safety: A Combined Fault Tree Analysis and Bayesian Network Approach—0
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Benchmark Results

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