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 1821–1830 of 2226 papers

TitleStatusHype
On Statistical Optimality of Variational Bayes—0
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators—0
Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise—0
Assumed Density Filtering Q-learningCode0
Approximations in the homogeneous Ising model—0
Episodic memory for continual model learning—0
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit—0
Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal NeuronsCode0
Molecular Clock Dating using MrBayes—0
Riemannian Stein Variational Gradient Descent for Bayesian InferenceCode0
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Benchmark Results

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