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Papers matching “kernel regression” 23

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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
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
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
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
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
Double Descent in Quantum Kernel Methods
2025 PRX Quantum article Computer Science Quantum Computing Algorithms and Architecture Open access

1

citations
Adiabatic Quantum Kitchen Sinks with Parallel Annealing for Remote Sensing Regression Problems
2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) conference-paper Computer Science Quantum Computing Algorithms and Architecture

Edoardo Pasetto, Morris Riedel, Kristel F. L. Michielsen, Gabriele Cavallaro

1

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
Residual bayesian attention networks for uncertainty quantification in regression tasks
2025 Scientific Reports article Computer Science Gaussian Processes and Bayesian Inference Open access

Youliang Chen, Wencan Guan, Rafig Azzam

10

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
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 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
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
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
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
Graph Learning with 1D Convolutions on Random Walks.
2021 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Jan Toenshoff, Martin Ritzert, Hinrikus Wolf, Martin Grohe

5

citations
SpeqNets: Sparsity-aware Permutation-equivariant Graph Networks
2022 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Gaurav Rattan, Sandra Kiefer, Siamak Ravanbakhsh

0

citations
Conditional Density Estimation with Histogram Trees
2024 arXiv (Cornell University) preprint Computer Science Data Mining Algorithms and Applications Open access

Lincen Yang, Matthijs van Leeuwen

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
A Comparative Analysis of Attention versus State-Space Models for In-Context Learning
2026 arXiv (Cornell University) preprint Computer Science Topic Modeling Open access

Enes Arda, Semih Çaycı, Atilla Eryılmaz

0

citations
YDANet: Leveraging YCbCr Color Space and Dual-Path Attention Network for Depth Completion
2026 International Conference on Multimedia Retrieval conference-paper Computer Science Advanced Vision and Imaging Open access

Jun Liu, Guoqiang Xiao, Michael S. Lew, Song Wu

0

citations

23 results