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Papers matching “kernel functions” 106

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Learning Functions and Uncertainty Sets Using Geometrically Constrained Kernel Regression
2022 2022 IEEE 61st Conference on Decision and Control (CDC) conference-paper Engineering Control Systems and Identification

Christian Fiedler, Carsten W. Scherer, Sebastian Trimpe

0

citations
Consistently smooth merit functions in algorithmic differentiable ray tracing for illumination design
2026 Optics Express article Computer Science Computer Graphics and Visualization Techniques Open access

Martin Pflaum, Hakon Johnsen

0

citations
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control
2024 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Mathias Oster, Luca Saluzzi, Tizian Wenzel

1

citations
A Comparison Study of Supervised Learning Techniques for the Approximation of High Dimensional Functions and Feedback Control
2024 Dynamic Games and Applications article Mathematics Tensor decomposition and applications Open access

Mathias Oster, Luca Saluzzi, Tizian Wenzel

2

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
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis
2022 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr

2

citations
Lipschitz and Hölder Continuity in Reproducing Kernel Hilbert Spaces
2023 RWTH Publications (RWTH Aachen) preprint Mathematics Approximation Theory and Sequence Spaces Open access

Christian Fiedler

0

citations
Points of non-linearity of functions generated by random neural networks
2023 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

0

citations
Unfolding recurrence by Green's functions for optimized reservoir computing
2020 arXiv (Cornell University) preprint Computer Science Neural Networks and Reservoir Computing Open access

Sandra Nestler, Christian Keup, David Dahmen, Matthieu Gilson, Holger Rauhut, Moritz Helias

0

citations
On genetic programming representations and fitness functions for interpretable dimensionality reduction
2022 Genetic and Evolutionary Computation Conference (GECCO) conference-paper Computer Science Evolutionary Algorithms and Applications Open access

Thomas Uriot, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman

18

citations
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis
2022 Lecture notes in computer science conference-paper Decision Sciences Advanced Bandit Algorithms Research

Kirill Antonov, Elena Raponi, Hao Wang, Carola Doerr

15

citations
On genetic programming representations and fitness functions for interpretable dimensionality reduction
2022 arXiv (Cornell University) preprint Computer Science Evolutionary Algorithms and Applications Open access

Thomas Uriot, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman

3

citations
Flexible Geological Modeling with Radial Basis Functions Integrating External Drift
2025 Mathematical Geosciences article Earth and Planetary Sciences Geological Modeling and Analysis Open access

Friedrich Carl, Peter Achtziger-Zupančič, Florian Wellmann

1

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

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

0

citations
Reproducing kernel Hilbert spaces in the mean field limit
2023 Kinetic and Related Models article Physics and Astronomy Model Reduction and Neural Networks Open access

Christian Fiedler, Michaël Herty, Michael Rom, Chiara Segala, Sebastian Trimpe

5

citations
Reproducing kernel Hilbert spaces in the mean field limit
2023 RWTH Publications (RWTH Aachen) article Computer Science Gaussian Processes and Bayesian Inference Open access

Christian Fiedler, Michaël Herty, Michael Rom, Chiara Segala, Sebastian Trimpe

1

citations
Kernel‐based online learning for real‐time voltage control in distribution networks
2020 IET Smart Grid article Engineering Optimal Power Flow Distribution Open access

Lisette Cupelli, Alejandro Lago Esteban, Ferdinanda Ponci, Antonello Monti

4

citations
Kernel method for gravity forward simulation in implicit probabilistic geologic modeling
2023 Geophysics article Earth and Planetary Sciences Geological Modeling and Analysis

Zhouji Liang, Miguel de la Varga, Florian Wellmann

3

citations
Applying physics-informed enhanced super-resolution generative adversarial networks to turbulent premixed combustion and engine-like flame kernel direct numerical simulation data
2023 Proceedings of the Combustion Institute article Engineering Combustion and flame dynamics Open access

Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch

31

citations
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data
2022 arXiv (Cornell University) preprint Engineering Combustion and flame dynamics Open access

Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch

0

citations
Shared network‐level functional alterations across substance use disorders: A multi‐level kernel density meta‐analysis of resting‐state functional connectivity studies
2022 Addiction Biology article Neuroscience Functional Brain Connectivity Studies Open access

Arezoo Taebi, Benjamin Becker, Benjamin Klugah‐Brown, Erik Roecher, Bharat B. Biswal, Jana Zweerings, +1 more

41

citations
Kernel Float: Unlocking Mixed-Precision GPU Programming
2025 ACM Transactions on Mathematical Software article Computer Science Numerical Methods and Algorithms Open access

Stijn Heldens, Ben van Werkhoven

3

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
The Near Infrared Imager and Slitless Spectrograph for JWST. V. Kernel Phase Imaging and Data Analysis
2023 Publications of the Astronomical Society of the Pacific article Physics and Astronomy Adaptive optics and wavefront sensing Open access

Jens Kammerer, Thomas Vandal, Deepashri Thatte, Frantz Martinache, Anand Sivaramakrishnan, Alexander Chaushev, +22 more

17

citations
The NNLO gluon beam function for jet-veto resummation
2024 Journal of High Energy Physics article Physics and Astronomy Particle physics theoretical and experimental studies Open access

Guido Bell, Kevin Brune, Goutam Das, Ding Yu Shao, Marcel Wald

4

citations