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Papers matching “Gaussian process regression” 27

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Scalable Gaussian Process Regression via Deterministic Trigonometric Features: Uniform Bounds for Safe Model Predictive Control
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Julius Jagdt, Johanna Menn, Sebastian Trimpe, Melanie N. Zeilinger, Anna Scampicchio

0

citations
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression
2021 Proceedings of the AAAI Conference on Artificial Intelligence conference-paper Computer Science Gaussian Processes and Bayesian Inference Open access cited by 1 patent

Christian Fiedler, Carsten W. Scherer, Sebastian Trimpe

48

citations
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression
2021 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Christian Fiedler, Carsten W. Scherer, Sebastian Trimpe

9

citations
Optimal recovery and uncertainty quantification for distributed Gaussian process regression
2022 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Amine Hadji, Tammo Hesselink, Botond Szabó

3

citations
Gaussian Process Regression for Maximum Entropy Distribution
2020 Journal of Computational Physics article Computer Science Gaussian Processes and Bayesian Inference Open access

Mohsen Sadr, Manuel Torrilhon, Hossein Gorji

14

citations
A Gaussian Process Regression IV Model for PV Outdoor Data
2025 Progress in Photovoltaics Research and Applications article Computer Science Solar Radiation and Photovoltaics Open access

Timon S. Vaas, Bart Elger Pieters, Evgenii Sovetkin, Andreas Gerber, Uwe Rau

0

citations
Gaussian Process Panel Modeling—Machine Learning Inspired Analysis of Longitudinal Panel Data
2020 Frontiers in Psychology article Computer Science Gaussian Processes and Bayesian Inference Open access

Julian David Karch, Andreas M. Brandmaier, Manuel C. Voelkle

19

citations
Can We Trust Bayesian Uncertainty Quantification from Gaussian Process Priors with Squared Exponential Covariance Kernel?
2021 SIAM/ASA Journal on Uncertainty Quantification article Computer Science Gaussian Processes and Bayesian Inference Open access

Amine Hadji, Botond Szabó

18

citations
Structure-preserving Gaussian Process Dynamics
2021 RWTH Publications (RWTH Aachen) conference-paper Computer Science Gaussian Processes and Bayesian Inference Open access

Katharina Ensinger, Friedrich Solowjow, Sebastian Ziesche, Sebastian Trimpe

1

citations
KernelMatmul: Scaling Gaussian Processes to Large Time Series
2025 Proceedings of the AAAI Conference on Artificial Intelligence conference-paper Computer Science Gaussian Processes and Bayesian Inference Open access

Tilman Hoffbauer, Holger H. Hoos, Jakob Bossek

0

citations
Gaussian processes and other kernel methods
2025 Cambridge University Press eBooks book-chapter Computer Science Gaussian Processes and Bayesian Inference

Borja Requena, Marylou Gabrié

12

citations
Adaptation Using Spatially Distributed Gaussian Processes
2025 Journal of the American Statistical Association article Computer Science Gaussian Processes and Bayesian Inference Open access

Botond Szabó, Amine Hadji, Aad van der Vaart

0

citations
Adaptation using spatially distributed Gaussian Processes
2023 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Botond Szabó, Amine Hadji, Aad van der Vaart

0

citations
Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Jakob Kramp, Javed Lindner, Moritz Helias

0

citations
Quantum-Assisted Multi-Output Gaussian Processes for Line Parameter Estimation in Power Systems
2026 IEEE Access article Computer Science Quantum Computing Algorithms and Architecture Open access

Priyanka Arkalgud Ganeshamurthy, Kumar Ghosh, Corey O’Meara, G. Cortiana, Jan Schiefelbein-Lach, Antonello Monti, +1 more

0

citations
Quantum-Assisted Multi-Output Gaussian Processes for Line Parameter Estimation in Power Systems
2026 RWTH Publications (RWTH Aachen) article Computer Science Quantum Computing Algorithms and Architecture Open access

Priyanka Arkalgud Ganeshamurthy, Kumar Ghosh, Corey O’Meara, G. Cortiana, Jan Schiefelbein-Lach, Antonello Monti, +1 more

0

citations
Transfer Learning of Surrogate Models via Domain Affine Transformation
2024 Genetic and Evolutionary Computation Conference (GECCO) conference-paper Computer Science Advanced Multi-Objective Optimization Algorithms Open access

Shuaiqun Pan, Diederick Vermetten, Manuel López‐Ibáñez, Thomas Bäck, Hao Wang

5

citations
CADET-Core: Version 6.0.0-alpha.4
2026 Zenodo (CERN European Organization for Nuclear Research) software Computer Science Modeling and Simulation Systems Open access

Jan Michael Breuer, Samuel Leweke, Johannes Schmölder, Antonia Berger, Hannah Lanzrath, Wendi Zhang, +1 more

0

citations
Machine learning with classical data
2025 Cambridge University Press eBooks book-chapter Computer Science Quantum Computing Algorithms and Architecture Open access

Sam McArdle, Connor T. Hann, Aleksander Kubica, Fernando G. S. L. Brandão

0

citations
Robot Learning With Crash Constraints
2021 IEEE Robotics and Automation Letters article Computer Science Reinforcement Learning in Robotics Open access

24

citations
Robot Learning With Crash Constraints
2021 RWTH Publications (RWTH Aachen) article Computer Science Reinforcement Learning in Robotics

Alonso Marco, Dominik Baumann, Majid Khadiv, Philipp Hennig, Ludovic Righetti

19

citations
On Boundary Conditions Parametrized by Analytic Functions
2022 Lecture notes in computer science conference-paper Computer Science Polynomial and algebraic computation

Markus Lange‐Hegermann, Daniel Robertz

1

citations
Kernel conditional tests from learning-theoretic bounds
2025 neural information processing systems conference-paper Computer Science Gaussian Processes and Bayesian Inference Open access

Pierre-François Massiani, Christian Fiedler, Lukas Haverbeck, Friedrich Solowjow, Sebastian Trimpe

0

citations
Structured learning of rigid‐body dynamics: A survey and unified view from a robotics perspective
2021 GAMM-Mitteilungen article Computer Science Reinforcement Learning in Robotics Open access

A. René Geist, Sebastian Trimpe

25

citations
On boundary conditions parametrized by analytic functions
2022 arXiv (Cornell University) preprint Computer Science Polynomial and algebraic computation Open access

Markus Lange‐Hegermann, Daniel Robertz

0

citations