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 2121–2130 of 2226 papers

TitleStatusHype
Exact Bayesian inference for off-line change-point detection in tree-structured graphical models—0
Excess risk analysis for epistemic uncertainty with application to variational inference—0
Exchangeable Variational Autoencoders with Applications to Genomic Data—0
Exoplanet Characterization using Conditional Invertible Neural Networks—0
Expectation Propagation performs a smoothed gradient descent—0
Experimentally detecting a quantum change point via Bayesian inference—0
Explainable Lane Change Prediction for Near-Crash Scenarios Using Knowledge Graph Embeddings and Retrieval Augmented Generation—0
Exploiting Dynamic Sparsity for Near-Field Spatial Non-Stationary XL-MIMO Channel Tracking—0
Exploiting Reducibility in Unsupervised Dependency Parsing—0
Exploration in Interactive Personalized Music Recommendation: A Reinforcement Learning Approach—0
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Benchmark Results

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