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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 1501–1510 of 2226 papers

Title	Date	Tasks	Status	Hype
Stein Variational Gradient Descent With Matrix-Valued Kernels	Oct 28, 2019	Bayesian Inference	CodeCode Available	0
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning	Oct 26, 2019	Bayesian InferenceGeneral Classification	—Unverified	0
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty	Oct 23, 2019	Bayesian InferenceComputed Tomography (CT)	CodeCode Available	0
Variational Predictive Information Bottleneck	Oct 23, 2019	Bayesian Inference	—Unverified	0
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models	Oct 23, 2019	Bayesian Inferenceregression	—Unverified	0
Safe-Bayesian Generalized Linear Regression	Oct 21, 2019	Bayesian Inferenceregression	—Unverified	0
Why bigger is not always better: on finite and infinite neural networks	Oct 17, 2019	Bayesian InferenceRepresentation Learning	—Unverified	0
Efficient Bayesian Inference for Nested Simulators	Oct 16, 2019	Bayesian Inference	—Unverified	0
AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms	Oct 16, 2019	Bayesian InferenceBenchmarking	CodeCode Available	0
Variationally Inferred Sampling Through a Refined Bound	Oct 16, 2019	Bayesian InferenceDensity Estimation	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