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 761–770 of 2226 papers

TitleStatusHype
Model-based Validation as Probabilistic InferenceCode0
Score Operator Newton transport—0
Thompson Sampling for Parameterized Markov Decision Processes with Uninformative Actions—0
Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition—0
Object based Bayesian full-waveform inversion for shear elastography—0
Sequential Experimental Design for Spectral Measurement: Active Learning Using a Parametric Model—0
The Compositional Structure of Bayesian Inference—0
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics—0
Location Tracking for Reconfigurable Intelligent Surfaces Aided Vehicle Platoons: Diverse Sparsities Inspired Approaches—0
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance—0
Show:102550
← PrevPage 77 of 223Next →

Benchmark Results

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