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 1381–1390 of 2226 papers

TitleStatusHype
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
Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory—0
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference—0
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Benchmark Results

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