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 311–320 of 2226 papers

TitleStatusHype
Integrating time-resolved nrf2 gene-expression data into a full GUTS model as a proxy for toxicodynamic damage in zebrafish embryo—0
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and ForecastingCode2
Electricity Spot Prices Forecasting Using Stochastic Volatility ModelsCode0
Domain Agnostic Conditional Invariant Predictions for Domain Generalization—0
Verbalized Probabilistic Graphical Modeling with Large Language Models—0
Stochastic full waveform inversion with deep generative prior for uncertainty quantification—0
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians—0
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation—0
Reparameterization invariance in approximate Bayesian inference—0
Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors—0
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Benchmark Results

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