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 1701–1710 of 2226 papers

TitleStatusHype
A Unified Kernel for Neural Network Learning—0
AutoBayes: A Compositional Framework for Generalized Variational Inference—0
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference—0
AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data—0
Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery—0
Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference—0
Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with Bayesian inference for uncertainty-based quality-control—0
Automatic Bayesian Density Analysis—0
Automatic maneuver detection and tracking of space objects in optical survey scenarios based on stochastic hybrid systems formulation—0
Automatic Variational Inference in Stan—0
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Benchmark Results

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