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Gaussian process
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221	C Blackwell Munksgaard, 2003 Copyright Tellus (2003), 55A, 126–147 Printed in UK. All rights reserved Add to Reading List Source URL: www.gfdl.noaa.gov Language: English - Date: 2008-02-04 13:56:07 Control theory Estimation theory Bayesian statistics Ensemble Kalman filter Data assimilation Kalman filter Covariance Sample mean and sample covariance Gaussian process Statistics Linear filters Covariance and correlation
222	Tests in Adaptive Regression via the Kac-Rice Formula Jonathan Taylor∗ , Joshua Loftus, Ryan J. Tibshirani Department of Statistics Stanford University Sequoia Hall Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2013-09-09 10:36:11 Regression analysis Econometrics Hypothesis testing Multivariate normal distribution Statistical hypothesis testing Variance Gaussian process Least squares T-statistic Statistics Normal distribution Parametric statistics
223	Fast Allocation of Gaussian Process Experts Trung V. Nguyen ANU & NICTA VTNGUYEN @ NICTA . COM . AU Add to Reading List Source URL: jmlr.org Language: English - Date: 2014-02-16 19:30:21 Statistical theory Gaussian process Mixture model Kriging Errors and residuals in statistics Statistics Regression analysis Machine learning
224	PSGP package installation instructions Remi Barillec January 21, 2012 1 Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 16:08:35 Gaussian Stochastic processes Gaussian process Interpolation
225	Package ‘psgp’ July 2, 2014 Version 0.3-6 Date 2014-05-08 Title Projected Spatial Gaussian Process (psgp) methods Author Ben Ingram , Remi Barillec Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 16:08:35 Variogram Maximum likelihood Gaussian process Variance Covariance function Interpolation Errors-in-variables models Estimation theory Statistics Geostatistics Kriging
226	Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence Generalizing Policy Advice with Gaussian Process Bandits for Dynamic Skill Improvement Jared Glover and Charlotte Zhu Add to Reading List Source URL: lis.csail.mit.edu Language: English - Date: 2014-08-08 12:56:02 Robot Cognitive robotics Table tennis Kinematics Mobile robot Machine learning Topspin Artificial intelligence Physics Humanoid robot Reinforcement learning Robotics
227	Gaussian Processes and Gene Regulation Multiple Transcription Factors, Networks and Model Organisms[removed]Background and Motivation. Gaussian Processes (Rasmussen and Williams, 2005) can provide a convenient framework Add to Reading List Source URL: www.stats.ox.ac.uk Language: English - Date: 2013-08-26 08:49:50 Molecular biology Genetics Transcription factors Gene regulatory network Gene Bioinformatics Gaussian process Phylogenetic footprinting Bayesian network Biology Gene expression Networks
228	OPTIMAL CHANGES OF GAUSSIAN MEASURES, WITH AN APPLICATIONS TO RESIMULATION Henry Schellhorn Abstract. We derive optimality conditions and calculate approximate solutions to the problem of determining the optimal speed of Add to Reading List Source URL: sites.cgu.edu Language: English - Date: 2014-01-28 14:45:18 Mathematical finance Probability theory Stochastic differential equations Martingale theory Gaussian measure Risk-neutral measure Ornstein–Uhlenbeck process Radon–Nikodym theorem Forward measure Statistics Mathematical analysis Stochastic processes
229	An Analytical Characterization for an Optimal Change of Gaussian Measures Henry Schellhorn Abstract. We consider two Gaussian measures. In the "initial" measure the state variable is Gaussian, with zero drift, and time-v Add to Reading List Source URL: sites.cgu.edu Language: English - Date: 2014-01-28 14:43:18 Stochastic differential equations Probability theory Ornstein–Uhlenbeck process Gaussian measure Optimal control Normal distribution Itō diffusion Statistics Mathematical analysis Stochastic processes
230	Gaussian Belief Space Planning with Discontinuities in Sensing Domains Sachin Patil, Yan Duan, John Schulman, Ken Goldberg, Pieter Abbeel Abstract— Discontinuities in sensing domains are common when planning for many r Add to Reading List Source URL: ieor.berkeley.edu Language: English - Date: 2014-02-16 20:56:29 Robot control Cartography Kalman filter Motion planning Simultaneous localization and mapping Partially observable Markov decision process Laplace transform Robotic mapping Trajectory optimization Mathematical analysis Statistics Control theory

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