gaussian process

Probabilistic Recurrent State-Space Models ICML 2018 Product Kernel Interpolation for Scalable Gaussian Processes AISTATS 2018 Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior NeurIPS 2018 Safe Active Learning for Time-Series Modeling with Gaussian Processes NeurIPS 2018 Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018 Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF) ICML 2018 Scalable Generalized Dynamic Topic Models AISTATS 2018 Scalable Hyperparameter Transfer Learning NeurIPS 2018 Scaling Gaussian Process Regression with Derivatives NeurIPS 2018 Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes AISTATS 2018 Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance NeurIPS 2018 Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation CoRL 2018 Stagewise Safe Bayesian Optimization with Gaussian Processes ICML 2018 State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018 Structured Gaussian Processes with Twin Multiple Kernel Learning ACML 2018 Structured Uncertainty Prediction Networks CVPR 2018 Tensor Regression Meets Gaussian Processes AISTATS 2018 The Transfer of Human Trust in Robot Capabilities across Tasks RSS 2018 Tight Regret Bounds for Bayesian Optimization in One Dimension ICML 2018 Transfer of Value Functions via Variational Methods NeurIPS 2018 Variational Bayesian Monte Carlo NeurIPS 2018 Variational Fourier Features for Gaussian Processes JMLR 2018 Variational Learning on Aggregate Outputs with Gaussian Processes NeurIPS 2018 Variational Network Inference: Strong and Stable with Concrete Support ICML 2018 A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space ACML 2017