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 81–90 of 2226 papers

TitleStatusHype
Can Transformers Learn Full Bayesian Inference in Context?Code1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Conditional score-based diffusion models for Bayesian inference in infinite dimensionsCode1
Continual Learning via Sequential Function-Space Variational InferenceCode1
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
Dangers of Bayesian Model Averaging under Covariate ShiftCode1
Antipodes of Label Differential Privacy: PATE and ALIBICode1
Bayesian continual learning and forgetting in neural networksCode1
Show:102550
← PrevPage 9 of 223Next →

Benchmark Results

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