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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

Relative Information Gain and Gaussian Process Regression ALT 2026
Practical Global and Local Bounds in Gaussian Process Regression via Chaining AAAI 2026
Optimizing Product Provenance Verification Using Data Valuation Methods AAAI 2026
SEA-PACE: Semi-Supervised Underwater Image Enhancement via Gaussian Process–Assisted Self-Paced Learning AAAI 2026
GS-LIVM: Real-Time Photo-Realistic LiDAR-Inertial-Visual Mapping with Gaussian Splatting ICCV 2025
Error Bounds for Gaussian Process Regression Under Bounded Support Noise with Applications to Safety Certification AAAI 2025
Asynchronous Distributed Gaussian Process Regression AAAI 2025
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood AAAI 2025
Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models JMLR 2025
CUQDS: Conformal Uncertainty Quantification Under Distribution Shift for Trajectory Prediction AAAI 2025
KernelMatmul: Scaling Gaussian Processes to Large Time Series AAAI 2025
Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval NIPS 2024
Kermut: Composite kernel regression for protein variant effects NIPS 2024
Lagrangian inspired polynomial estimator for black-box learning and control of underactuated systems L4DC 2024
Sample-Constrained Black Box Optimization for Audio Personalization AAAI 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels AISTATS 2024
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression AISTATS 2024
Nearly Optimal Approximation of Matrix Functions by the Lanczos Method NIPS 2024
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics JMLR 2023
Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning L4DC 2023
Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data L4DC 2023
Robust and Scalable Gaussian Process Regression and Its Applications CVPR 2023
Maximum likelihood estimation in Gaussian process regression is ill-posed JMLR 2023
Implicit Manifold Gaussian Process Regression NIPS 2023
Surveillance Evasion Through Bayesian Reinforcement Learning AISTATS 2023