Gaussian Processes

BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic AAAI 2020 Conjugate Gradients for Kernel Machines JMLR 2020 Continual Deep Learning by Functional Regularisation of Memorable Past NeurIPS 2020 Data-driven confidence bands for distributed nonparametric regression COLT 2020 Deep Gaussian Markov Random Fields ICML 2020 Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare AAAI 2020 Dynamic Embedding on Textual Networks via a Gaussian Process AAAI 2020 Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations ICML 2020 Enriched mixtures of generalised Gaussian process experts AISTATS 2020 GaSPing for Utility AAAI 2020 GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020 GP-VAE: Deep Probabilistic Time Series Imputation AISTATS 2020 Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights NeurIPS 2020 Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020 Influenza Forecasting Framework based on Gaussian Processes ICML 2020 Interpretable Deep Gaussian Processes with Moments AISTATS 2020 Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020 Learning in the Wild with Incremental Skeptical Gaussian Processes IJCAI 2020 Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots RSS 2020 Matérn Gaussian Processes on Riemannian Manifolds NeurIPS 2020 Multi-Speaker Text-to-Speech Synthesis Using Deep Gaussian Processes Interspeech 2020 Multi-task Causal Learning with Gaussian Processes NeurIPS 2020 Neuronal Gaussian Process Regression NeurIPS 2020 Non-reversible Gaussian processes for identifying latent dynamical structure in neural data NeurIPS 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems AAAI 2020