Gaussian Processes

Gaussian Processes is a powerful framework for several machine learning tasks such as regression, classification and inference. Given a finite set of input output training data that is generated out of a fixed (but possibly unknown) function, the framework models the unknown function as a stochastic process such that the training outputs are a finite number of jointly Gaussian random variables, whose properties can then be used to infer the statistics (the mean and variance) of the function at test values of input.

Source: Sequential Randomized Matrix Factorization for Gaussian Processes: Efficient Predictions and Hyper-parameter Optimization

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1826–1850 of 1963 papers

Title	Date	Tasks	Status	Hype
Gaussian Process Random Fields	Oct 31, 2015	BIG-bench Machine LearningGaussian Processes	CodeCode Available	0
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes	Oct 27, 2015	Gaussian ProcessesGeneral Classification	—Unverified	0
The Human Kernel	Oct 26, 2015	Gaussian Processes	—Unverified	0
Optimization as Estimation with Gaussian Processes in Bandit Settings	Oct 21, 2015	Bayesian OptimizationGaussian Processes	CodeCode Available	0
Optimization for Gaussian Processes via Chaining	Oct 19, 2015	Gaussian ProcessesStochastic Optimization	—Unverified	0
p-Markov Gaussian Processes for Scalable and Expressive Online Bayesian Nonparametric Time Series Forecasting	Oct 9, 2015	Gaussian Processesregression	—Unverified	0
Fast Gaussian Process Regression for Big Data	Sep 17, 2015	Gaussian Processesregression	—Unverified	0
Modeling and interpolation of the ambient magnetic field by Gaussian processes	Sep 15, 2015	Gaussian Processes	—Unverified	0
Semi-described and semi-supervised learning with Gaussian processes	Sep 3, 2015	Gaussian ProcessesMissing Values	—Unverified	0
Steps Toward Deep Kernel Methods from Infinite Neural Networks	Aug 20, 2015	Gaussian Processes	—Unverified	0
Learning Structural Kernels for Natural Language Processing	Aug 10, 2015	Gaussian ProcessesHyperparameter Optimization	—Unverified	0
String and Membrane Gaussian Processes	Jul 24, 2015	Bayesian InferenceGaussian Processes	—Unverified	0
Fast Adaptive Weight Noise	Jul 19, 2015	Gaussian Processes	—Unverified	0
Fast Approximate Bayesian Computation for Estimating Parameters in Differential Equations	Jul 17, 2015	Gaussian ProcessesModel Selection	—Unverified	0
Anomaly Detection and Removal Using Non-Stationary Gaussian Processes	Jul 2, 2015	Anomaly DetectionEEG	—Unverified	0
MCMC for Variationally Sparse Gaussian Processes	Jun 12, 2015	FormGaussian Processes	—Unverified	0
Mondrian Forests for Large-Scale Regression when Uncertainty Matters	Jun 11, 2015	Bayesian OptimizationGaussian Processes	CodeCode Available	0
Provable Bayesian Inference via Particle Mirror Descent	Jun 9, 2015	Bayesian InferenceGaussian Processes	—Unverified	0
String Gaussian Process Kernels	Jun 7, 2015	Gaussian Processes	—Unverified	0
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models	Jun 7, 2015	Gaussian ProcessesState Space Models	—Unverified	0
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	Jun 6, 2015	Bayesian InferenceDeep Reinforcement Learning	CodeCode Available	1
Optimal change point detection in Gaussian processes	Jun 3, 2015	Change Point DetectionGaussian Processes	—Unverified	0
Batch Bayesian Optimization via Local Penalization	May 29, 2015	Bayesian OptimisationBayesian Optimization	CodeCode Available	0
A Sparse Gaussian Process Framework for Photometric Redshift Estimation	May 20, 2015	Gaussian ProcessesPhotometric Redshift Estimation	—Unverified	0
Necessary and Sufficient Conditions for Surrogate Functions of Pareto Frontiers and Their Synthesis Using Gaussian Processes	May 19, 2015	Gaussian Processesvalid	—Unverified	0

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ICKy, periodic	Root mean square error (RMSE)	0.03	—	Unverified