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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 1521–1530 of 2226 papers

Title	Date	Tasks	Status	Hype
Variational Tracking and Prediction with Generative Disentangled State-Space Models	Oct 14, 2019	Bayesian InferencePosition	—Unverified	0
Bayesian Integration of Multi-resolutional Grid Codes for Spatial Cognition	Oct 14, 2019	Bayesian InferenceHippocampus	—Unverified	0
Distilling Importance Sampling for Likelihood Free Inference	Oct 8, 2019	Bayesian InferenceEpidemiology	CodeCode Available	0
Stochastic triangular mesh mapping: A terrain mapping technique for autonomous mobile robots	Oct 8, 2019	Bayesian Inference	—Unverified	0
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction	Oct 7, 2019	Bayesian InferenceMolecular Property Prediction	—Unverified	0
Bayesian Learning-Based Adaptive Control for Safety Critical Systems	Oct 5, 2019	Autonomous VehiclesBayesian Inference	CodeCode Available	0
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization	Oct 4, 2019	Bayesian InferenceVariational Inference	—Unverified	0
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models	Oct 3, 2019	Bayesian InferenceDeep Learning	—Unverified	0
Inference of a mesoscopic population model from population spike trains	Oct 3, 2019	Bayesian Inference	CodeCode Available	0
The Neural Moving Average Model for Scalable Variational Inference of State Space Models	Oct 2, 2019	Bayesian InferenceNormalising Flows	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