gaussian process

Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Kernels and learning curves for Gaussian process regression on random graphs NeurIPS 2009 Learning GP-BayesFilters via Gaussian process latent variable models RSS 2009 Stable and Efficient Gaussian Process Calculations JMLR 2009 Variational Gaussian-process factor analysis for modeling spatio-temporal data NeurIPS 2009 Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes NeurIPS 2008 Adapting to a Market Shock: Optimal Sequential Market-Making NeurIPS 2008 Approximations for Binary Gaussian Process Classification JMLR 2008 Bayesian Kernel Shaping for Learning Control NeurIPS 2008 Efficient Sampling for Gaussian Process Inference using Control Variables NeurIPS 2008 Gas Distribution Modeling using Sparse Gaussian Process Mixture Models RSS 2008 Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity NeurIPS 2008 Modeling human function learning with Gaussian processes NeurIPS 2008 Multi-task Gaussian Process Learning of Robot Inverse Dynamics NeurIPS 2008 Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies JMLR 2008 Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes NeurIPS 2008 Sparse Convolved Gaussian Processes for Multi-output Regression NeurIPS 2008 The Gaussian Process Density Sampler NeurIPS 2008 Variational Mixture of Gaussian Process Experts NeurIPS 2008 Augmented Functional Time Series Representation and Forecasting with Gaussian Processes NeurIPS 2007 Bayesian Co-Training NeurIPS 2007 Bundle Methods for Machine Learning NeurIPS 2007 Characterizing the Function Space for Bayesian Kernel Models JMLR 2007 Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders RSS 2007 Gaussian Process Models for Link Analysis and Transfer Learning NeurIPS 2007