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 341–350 of 2226 papers

TitleStatusHype
Constrained belief updates explain geometric structures in transformer representations—0
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation—0
Optimal Subspace Inference for the Laplace Approximation of Bayesian Neural NetworksCode0
Eliciting Language Model Behaviors with Investigator Agents—0
Leveraging Joint Predictive Embedding and Bayesian Inference in Graph Self Supervised LearningCode0
Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems—0
Biogeochemistry-Informed Neural Network (BINN) for Improving Accuracy of Model Prediction and Scientific Understanding of Soil Organic Carbon—0
VKFPos: A Learning-Based Monocular Positioning with Variational Bayesian Extended Kalman Filter IntegrationCode0
BARNN: A Bayesian Autoregressive and Recurrent Neural Network—0
Beyond Prior Limits: Addressing Distribution Misalignment in Particle Filtering—0
Show:102550
← PrevPage 35 of 223Next →

Benchmark Results

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