gaussian process

Active Incremental Learning of Robot Movement Primitives CoRL 2017 A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017 Asynchronous Distributed Variational Gaussian Process for Regression ICML 2017 A Trust-based Mixture of Gaussian Processes Model for Reliable Regression in Participatory Sensing IJCAI 2017 A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation JMLR 2017 Batched High-dimensional Bayesian Optimization via Structural Kernel Learning ICML 2017 Bayesian Inference for Spatio-temporal Spike-and-Slab Priors JMLR 2017 Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes NeurIPS 2017 Bayesian Learning of Dynamic Multilayer Networks JMLR 2017 Bayesian Optimization with Gradients NeurIPS 2017 Bayesian Optimization with Tree-structured Dependencies ICML 2017 Convolutional Gaussian Processes NeurIPS 2017 Correlational Gaussian Processes for Cross-Domain Visual Recognition CVPR 2017 Cross-Spectral Factor Analysis NeurIPS 2017 Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs NeurIPS 2017 Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NeurIPS 2017 Distributed Batch Gaussian Process Optimization ICML 2017 Distribution of Gaussian Process Arc Lengths AISTATS 2017 Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes NeurIPS 2017 Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NeurIPS 2017 Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments CoRL 2017 Fast Bayesian Intensity Estimation for the Permanental Process ICML 2017 Forecast the Plausible Paths in Crowd Scenes IJCAI 2017 Gaussian process based nonlinear latent structure discovery in multivariate spike train data NeurIPS 2017 GPflow: A Gaussian Process Library using TensorFlow JMLR 2017