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 101–110 of 2226 papers

TitleStatusHype
How To Make Your Cell Tracker Say "I dunno!"—0
Efficient Membership Inference Attacks by Bayesian Neural Network—0
HIF: Height Interval Filtering for Efficient Dynamic Points Removal—0
From Theory to Application: A Practical Introduction to Neural Operators in Scientific ComputingCode1
Poisoning Bayesian Inference via Data Deletion and Replication—0
Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference—0
Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy—0
Bayesian inference for dynamic spatial quantile models with interactive effects—0
From Understanding the World to Intervening in It: A Unified Multi-Scale Framework for Embodied CognitionCode0
Multi-model Stochastic Particle-based Variational Bayesian Inference for Multiband Delay Estimation—0
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Benchmark Results

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