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Bayesian Inference

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2031–2040 of 2226 papers

Title	Date	Tasks	Status	Hype
Bayesian inference for spatio-temporal spike-and-slab priors	Sep 15, 2015	Bayesian Inference	—Unverified	0
Modeling sequences and temporal networks with dynamic community structures	Sep 15, 2015	Bayesian Inference	—Unverified	0
Learning without Recall by Random Walks on Directed Graphs	Sep 14, 2015	Bayesian Inference	—Unverified	0
Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias	Sep 3, 2015	Bayesian Inferencefeature selection	—Unverified	0
Varying-coefficient models with isotropic Gaussian process priors	Aug 28, 2015	Bayesian Inference	—Unverified	0
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors	Aug 18, 2015	Bayesian Inference	—Unverified	0
Towards Machine Wald	Aug 10, 2015	Bayesian InferenceStochastic Optimization	—Unverified	0
Orthogonal parallel MCMC methods for sampling and optimization	Jul 30, 2015	Bayesian Inference	—Unverified	0
String and Membrane Gaussian Processes	Jul 24, 2015	Bayesian InferenceGaussian Processes	—Unverified	0
Scalable Bayesian Inference for Excitatory Point Process Networks	Jul 12, 2015	Bayesian InferenceVariational Inference	CodeCode Available	0

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	F-SWA	Accuracy	83.61	—	Unverified
2	F-SWAG	Accuracy	80.93	—	Unverified