SOTAVerified

Bayesian Inference

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 771–780 of 2226 papers

TitleStatusHype
Attention-Driven Hierarchical Reinforcement Learning with Particle Filtering for Source Localization in Dynamic Fields—0
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation—0
Density Estimation via Bayesian Inference Engines—0
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning—0
A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics—0
Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation—0
Biases and Variability from Costly Bayesian Inference—0
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation—0
A New Parameterized Family of Stochastic Particle Flow Filters—0
Bézier Curve Gaussian Processes—0
Show:102550
← PrevPage 78 of 223Next →

Benchmark Results

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