gaussian process

Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning NeurIPS 2020 Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations ICML 2020 Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees NeurIPS 2020 Enriched mixtures of generalised Gaussian process experts AISTATS 2020 Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability AISTATS 2020 Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization NeurIPS 2020 Federated Bayesian Optimization via Thompson Sampling NeurIPS 2020 Functional Regularisation for Continual Learning with Gaussian Processes ICLR 2020 GaSPing for Utility AAAI 2020 Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective NeurIPS 2020 Generalized probabilistic principal component analysis of correlated data JMLR 2020 GPIRT: A Gaussian Process Model for Item Response Theory UAI 2020 GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020 GP-VAE: Deep Probabilistic Time Series Imputation AISTATS 2020 Healing Products of Gaussian Process Experts ICML 2020 Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights NeurIPS 2020 Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020 High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds NeurIPS 2020 Incremental learning of EMG-based control commands using Gaussian Processes CoRL 2020 Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations AAAI 2020 Influenza Forecasting Framework based on Gaussian Processes ICML 2020 Knowing The What But Not The Where in Bayesian Optimization ICML 2020 Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020 Learning Fair Representations for Kernel Models AISTATS 2020 Learning in the Wild with Incremental Skeptical Gaussian Processes IJCAI 2020