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 271–280 of 2226 papers

TitleStatusHype
Bayesian Robust Aggregation for Federated LearningCode0
Ensemble Kalman filter for uncertainty in human language comprehension—0
Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties—0
Data-driven Approach for Interpolation of Sparse DataCode0
Confidence in Large Language Model Evaluation: A Bayesian Approach to Limited-Sample Challenges—0
Array Partitioning Based Near-Field Attitude and Location Estimation—0
Position: Bayesian Statistics Facilitates Stakeholder Participation in Evaluation of Generative AI—0
Bayesian Sensing for Time-Varying Channels in ISAC Systems—0
Segmentation with Noisy Labels via Spatially Correlated DistributionsCode0
Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions—0
Show:102550
← PrevPage 28 of 223Next →

Benchmark Results

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