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gaussian process regression

133 papers

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Also known as

GPR GP REGRESSION

Co-occurring keywords

gaussian process (1200) bayesian inference (1907) uncertainty quantification (1393) variational inference (2069) kernel methods (1097) sparse approximation (76) sparse gaussian process (27) kernel approximation (100) hyperparameter optimization (406) online learning (1777)

Papers

Implicit Manifold Gaussian Process Regression NIPS 2023
Understanding Dynamic Tactile Sensing for Liquid Property Estimation RSS 2022
Giga-scale Kernel Matrix-Vector Multiplication on GPU NIPS 2022
Scalable Gaussian-process regression and variable selection using Vecchia approximations JMLR 2022
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations JMLR 2022
Gauss-Legendre Features for Gaussian Process Regression JMLR 2022
Sparse Additive Gaussian Process Regression JMLR 2022
Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression JMLR 2022
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators L4DC 2022
How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022
Contraction rates for sparse variational approximations in Gaussian process regression JMLR 2022
Gaussian Process-Based Real-Time Learning for Safety Critical Applications ICML 2021
Consistency of Gaussian Process Regression in Metric Spaces JMLR 2021
Data-Efficient Reinforcement Learning for Malaria Control IJCAI 2021
Geometric convergence of elliptical slice sampling ICML 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression AAAI 2021
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric L4DC 2021
Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system L4DC 2021
Sequence-to-Sequence Learning for Deep Gaussian Process Based Speech Synthesis Using Self-Attention GP Layer INTERSPEECH 2021
Safe Bayesian Optimisation for Controller Design by Utilising the Parameter Space Approach L4DC 2021
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients ICML 2021
Active Preference-Based Gaussian Process Regression for Reward Learning RSS 2020
Generalised Bayesian Filtering via Sequential Monte Carlo NIPS 2020
BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic AAAI 2020
Scalable Gaussian Process Regression Networks IJCAI 2020