Journal of Machine Learning Research–1704 Submitted 8/05; PublishedAssessing Approximate Inference for Binary Gaussian Process Classification

Source URL: www.jmlr.org

Gaussian Process Kernels for Pattern Discovery and Extrapolation Andrew Gordon Wilson Department of Engineering, University of Cambridge, Cambridge, UK

Source URL: jmlr.org

The Change Point Kernel Andrew Gordon Wilson November 12, 2013 Saatchi et aland Osborne (2010), for instance, have introduced Gaussian process models for change points. In this note, we discuss how the Gaussian

Source URL: www.cs.cmu.edu

Gaussian Process Regression Networks Supplementary Material Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani University of Cambridge , , In this supplementary

Source URL: www.cs.cmu.edu

Moduli of Continuity of Local Times of Strongly Symmetric Markov Processes via Gaussian Processes 1. Introduction. In this paper we show that the moduli of continuity of the local times of a large class of Markov process

Source URL: www.math.csi.cuny.edu

Spatial Gaussian Process (GP) models for Massive Geostatistical Datasets Spatial Gaussian Process (GP) models—subsume kriging—for point-referenced geospatial datasets provide a statistically valid framework for predi

Source URL: carbon.nasa.gov

Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods Yaakov Engel∗ AICML, Dept. of Computing Science University of Alberta

Source URL: papers.nips.cc

A prior near-ignorance Gaussian Process model for nonparametric regression Francesca Mangili Istituto Dalle Molle di studi sull’Intelligenza Artificiale (IDSIA), Scuola universitaria professionale della Svizzera italia

Source URL: ipg.idsia.ch

PROBABILISTIC MODELING OF GENE REGULATORY NETWORKS FROM DATA Thesis submitted for the degree “Doctor of Philosophy”

Source URL: www.cs.huji.ac.il

• Statistics
• Networks
• Learning
• Systems science
• Statistical models
• Systems biology
• Machine learning
• Bayesian network
• Gene regulatory network
• Nir Friedman
• Gaussian process
• Nonlinear dimensionality reduction

Gaussian sampling by local perturbations George Papandreou Department of Statistics University of California, Los Angeles

Source URL: www.stat.ucla.edu

• Statistics
• Statistical models
• Stochastic processes
• Linear filters
• Bayesian statistics
• Estimation theory
• Gibbs sampling
• Normal distribution
• Kalman filter
• Mixture model
• Bayesian network
• Gaussian process