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 1721–1730 of 2226 papers

TitleStatusHype
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach—0
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE)—0
Stochastic Gradient MCMC for State Space ModelsCode0
Good Initializations of Variational Bayes for Deep Models—0
EMHMM Simulation Study—0
Metropolis-Hastings view on variational inference and adversarial training—0
The Deep Weight PriorCode0
Bayesian Inference of Self-intention Attributed by Observer—0
Uncertainty in Neural Networks: Approximately Bayesian EnsemblingCode0
Dropout as a Structured Shrinkage PriorCode0
Show:102550
← PrevPage 173 of 223Next →

Benchmark Results

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