SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1881–1890 of 2226 papers

TitleStatusHype
Dirichlet Bayesian Network Scores and the Maximum Relative Entropy Principle—0
PROBE-GK: Predictive Robust Estimation using Generalized Kernels—0
Chance, long tails, and inference: a non-Gaussian, Bayesian theory of vocal learning in songbirds—0
Learning to Draw Samples with Amortized Stein Variational Gradient Descent—0
Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior—0
Comparative Study of Inference Methods for Bayesian Nonnegative Matrix FactorisationCode0
Vectorial Dimension Reduction for Tensors Based on Bayesian Inference—0
Stochastic Gradient MCMC Methods for Hidden Markov Models—0
BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks—0
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing—0
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Benchmark Results

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