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 581–590 of 2226 papers

TitleStatusHype
Recursive Metropolis-Hastings Naming Game: Symbol Emergence in a Multi-agent System based on Probabilistic Generative Models—0
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in KenyaCode0
Low-rank extended Kalman filtering for online learning of neural networks from streaming dataCode1
Sparse species interactions reproduce abundance correlation patterns in microbial communities—0
Parallelized Acquisition for Active Learning using Monte Carlo SamplingCode1
A Bayesian sparse factor model with adaptive posterior concentration—0
Conditional score-based diffusion models for Bayesian inference in infinite dimensionsCode1
Bayesian inference and neural estimation of acoustic wave propagation—0
Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming ApproachCode1
Improving Neural Additive Models with Bayesian PrinciplesCode0
Show:102550
← PrevPage 59 of 223Next →

Benchmark Results

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