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 876–900 of 2226 papers

TitleStatusHype
Efficient posterior inference & generalization in physics-based Bayesian inference with conditional GANs—0
Efficient Bayesian Inference for a Gaussian Process Density Model—0
Efficient Reinforcement Learning with Large Language Model Priors—0
Bayesian inference for the mixed conditional heteroskedasticity model—0
Efficient transfer learning and online adaptation with latent variable models for continuous control—0
Efficient Weight-Space Laplace-Gaussian Filtering and Smoothing for Sequential Deep Learning—0
EinSteinVI: General and Integrated Stein Variational Inference—0
A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series—0
Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems—0
Efficient Attack Graph Analysis through Approximate Inference—0
Elements of Sequential Monte Carlo—0
Eliciting Language Model Behaviors with Investigator Agents—0
Embarrassingly parallel MCMC using deep invertible transformations—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Efficient Approximate Inference with Walsh-Hadamard Variational Inference—0
Bayesian Inference for Structured Spike and Slab Priors—0
A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation—0
Efficient acquisition rules for model-based approximate Bayesian computation—0
Bayesian inference for spatio-temporal spike-and-slab priors—0
Dynamics on Lie groups with applications to attitude estimation—0
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data—0
Bayesian Inference for Radar Imagery Based Surveillance—0
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
Ensemble Kalman filter for uncertainty in human language comprehension—0
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization—0
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Benchmark Results

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