gaussian process

Input Warping for Bayesian Optimization of Non-Stationary Functions ICML 2014 Locally Adaptive Factor Processes for Multivariate Time Series JMLR 2014 Mind the Nuisance: Gaussian Process Classification using Privileged Noise NeurIPS 2014 Modeling High-Dimensional Humans for Activity Anticipation using Gaussian Process Latent CRFs RSS 2014 Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes ICML 2014 Nonparametric Bayesian inference on multivariate exponential families NeurIPS 2014 On Prior Distributions and Approximate Inference for Structured Variables NeurIPS 2014 Persistent Monitoring of Stochastic Spatio-temporal Phenomena with a Small Team of Robots RSS 2014 Probabilistic Differential Dynamic Programming NeurIPS 2014 Probabilistic ODE Solvers with Runge-Kutta Means NeurIPS 2014 Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics AISTATS 2014 Quantized Estimation of Gaussian Sequence Models in Euclidean Balls NeurIPS 2014 Sample Efficient Reinforcement Learning with Gaussian Processes ICML 2014 Scalable Collaborative Bayesian Preference Learning AISTATS 2014 Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications ICML 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Student-t Processes as Alternatives to Gaussian Processes AISTATS 2014 Tilted Variational Bayes AISTATS 2014 Tree-structured Gaussian Process Approximations NeurIPS 2014 Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning JMLR 2014 Variational Gaussian Process State-Space Models NeurIPS 2014 Active Learning for Multi-Objective Optimization ICML 2013 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 Approximate inference in latent Gaussian-Markov models from continuous time observations NeurIPS 2013 A Video Representation Using Temporal Superpixels CVPR 2013