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Papers matching “kernel functions” 47

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Learning Functions and Uncertainty Sets Using Geometrically Constrained Kernel Regression
2022 Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes conference-paper Computer Science Gaussian Processes and Bayesian Inference

Christian Fiedler, Carsten W. Scherer, Sebastian Trimpe

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 Computer Science Adaptive Dynamic Programming Control 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
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
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
Deep kernel video approximation for unsupervised action segmentation
2026 arXiv (Cornell University) preprint Computer Science Human Pose and Action Recognition Open access

Silvia L. Pintea, Jouke Dijkstra

0

citations
Deep kernel video approximation for unsupervised action segmentation
2026 arXiv (Cornell University) preprint Computer Science Human Pose and Action Recognition Open access

Silvia L. Pintea, Jouke Dijkstra

0

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
Reproducing kernel Hilbert spaces in the mean field limit
2023 Kinetic and Related Models article Computer Science Gaussian Processes and Bayesian Inference 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
Universality and kernel-adaptive training for classically trained, quantum-deployed generative models
2025 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Andrii Kurkin, Susanne Pielawa, Hao Wang, Vedran Dunjko

0

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
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
Critical feature learning in deep neural networks
2024 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Javed Lindner, David Dahmen, Zohar Ringel, M. Krämer, Moritz Helias

0

citations
Support Vector Machines
2020 Springer eBooks book-chapter Computer Science Machine Learning and Algorithms

Rudolf Mathar, Gholamreza Alirezaei, Emilio Rafael Balda, Arash Behboodi

24

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
High-Configurability for Operating Systems
2024 RoEduNet Conference: Networking in Education and Research (RoEduNet) conference-paper Computer Science Advanced Software Engineering Methodologies

Tiberiu Deak, Razvan adrian Deaconescu, M. Kröning, Antonello Monti

0

citations
Convolutional Neural Networks as 2-D systems
2023 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Dennis Gramlich, Patricia Pauli, Carsten W. Scherer, Frank Allgöwer, Christian Ebenbauer

3

citations
A unified weighting framework for evaluating nearest neighbour classification
2025 Fuzzy Sets and Systems article Computer Science Rough Sets and Fuzzy Logic Open access

Oliver Urs Lenz, Henri Bollaert, Chris Cornelis

3

citations
A unified weighting framework for evaluating nearest neighbour classification
2023 arXiv (Cornell University) preprint Computer Science Machine Learning and Data Classification Open access

Oliver Urs Lenz, Henri Bollaert, Chris Cornelis

0

citations
Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets
2020 Nature Communications article Computer Science Machine Learning in Healthcare Open access

Marc-André Schulz, B.T. Thomas Yeo, Joshua T Vogelstein, Janaina Mourao-Miranada, Jakob Nikolas Kather, Konrad Paul Kording, +2 more

312

citations