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Gaussian Processes

570 papers

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Papers

Parametric Gaussian Process Regressors ICML 2020
Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations ICML 2020
Deep Gaussian Markov Random Fields ICML 2020
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020
Influenza Forecasting Framework based on Gaussian Processes ICML 2020
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020
Scalable Gaussian Process Regression Networks IJCAI 2020
Learning in the Wild with Incremental Skeptical Gaussian Processes IJCAI 2020
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables IJCAI 2020
Bayesian Optimization using Pseudo-Points IJCAI 2020
Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract) IJCAI 2020
Multi-Speaker Text-to-Speech Synthesis Using Deep Gaussian Processes INTERSPEECH 2020
Conjugate Gradients for Kernel Machines JMLR 2020
Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020
Semi-parametric Learning of Structured Temporal Point Processes JMLR 2020
On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach JMLR 2020
Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models L4DC 2020
Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020
On Simulation and Trajectory Prediction with Gaussian Process Dynamics L4DC 2020
Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots RSS 2020
Sensor Placement for Spatial Gaussian Processes with Integral Observations UAI 2020
Multi-resolution Multi-task Gaussian Processes NIPS 2019
Exact Gaussian Processes on a Million Data Points NIPS 2019
Bayesian Optimization under Heavy-tailed Payoffs NIPS 2019
Sequential Neural Processes NIPS 2019