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Papers matching “adaptive kernel” 53

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Adaptive greedy algorithm for moderately large dimensions in kernel conditional density estimation
2021 arXiv (Cornell University) preprint Mathematics Statistical Methods and Inference Open access

Minh-Lien Jeanne Nguyen, Claire Lacour, Vincent Rivoirard

2

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

14

citations
Scalable Signature Kernel Computations for Long Time Series via Local Neumann Series Expansions
2025 arXiv (Cornell University) preprint Computer Science Topological and Geometric Data Analysis Open access

Matthew Tamayo-Rios, Rima Alaifari

1

citations
Compatibility of Higher-Order Slow-Manifold Reduction and Continuum Limits in Adaptive Networks
2026 arXiv (Cornell University) preprint Physics and Astronomy Nonlinear Dynamics and Pattern Formation Open access

Christian Kuehn, Fergal Murphy, Jan-Eric Sulzbach

0

citations
From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning
2025 JuSER (Forschungszentrum Jülich) conference-paper Computer Science Neural Networks and Applications Open access

Noa Rubin, Javed Lindner, David Dahmen, Inbar Seroussi, Zohar Ringel, Michael Krämer, +1 more

14

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
On the implementation and execution of adaptive streaming applications modeled as MADF
2020 International Workshop on Software and Compilers for Embedded Systems (SCOPES) conference-paper Computer Science Real-Time Systems Scheduling Open access

Sobhan Niknam, Peng Wang, Todor P. Stefanov

0

citations
Seidr update: photonic 'black magic' for high-contrast interferometry using kernel-nulling and photonic lanterns
2026 arXiv (Cornell University) preprint Physics and Astronomy Adaptive optics and wavefront sensing Open access

Nathan K. Long, Daniel S. Dahl, Christopher H. Betters, Julia J. Bryant, Nick Cvetojević, Michael Ireland, +10 more

0

citations
Seidr update: photonic 'black magic' for high-contrast interferometry using kernel-nulling and photonic lanterns
2026 arXiv (Cornell University) preprint Physics and Astronomy Adaptive optics and wavefront sensing Open access

Nathan K. Long, Daniel S. Dahl, Christopher H. Betters, Julia J. Bryant, Nick Cvetojević, Michael Ireland, +10 more

0

citations
FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series
2024 Astronomy and Astrophysics article Physics and Astronomy Stellar, planetary, and galactic studies Open access

Fiorenzo Stoppa, C. Johnston, Eric Cator, Gijs Nelemans, P. Groot

1

citations
FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series
2023 arXiv (Cornell University) preprint Physics and Astronomy Stellar, planetary, and galactic studies Open access

Fiorenzo Stoppa, C. Johnston, Eric Cator, Gijs Nelemans, P. Groot

0

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
Lecture notes: From Gaussian processes to feature learning
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Moritz Helias, Javed Lindner, Lars Schutzeichel, Zohar Ringel

2

citations
Unsupervised Discretization by Two-dimensional MDL-based Histogram
2020 arXiv (Cornell University) preprint Computer Science Data Mining Algorithms and Applications Open access

Lincen Yang, Mitra Baratchi, Matthijs van Leeuwen

2

citations
Computational challenges in materials science
2020 RWTH Publications (RWTH Aachen) dissertation Computer Science Matrix Theory and Algorithms Open access

Jan Winkelmann

0

citations
Automatic Nonlinear MPC Approximation With Closed-Loop Guarantees
2025 IEEE Transactions on Automatic Control article Engineering Advanced Control Systems Optimization Open access

Abdullah Tokmak, Christian Fiedler, Melanie N. Zeilinger, Sebastian Trimpe, Johannes Köhler

14

citations
Automatic nonlinear MPC approximation with closed-loop guarantees
2023 arXiv (Cornell University) preprint Engineering Advanced Control Systems Optimization Open access

Abdullah Tokmak, Christian Fiedler, Melanie N. Zeilinger, Sebastian Trimpe, Johannes Köhler

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
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
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

8

citations
Bayesian experimental design in production engineering: a comprehensive performance and robustness study
2026 Frontiers in Manufacturing Technology article Decision Sciences Optimal Experimental Design Methods Open access

Lars Leyendecker, Ana Maria Gonzalez Degetau, Katharina Bata, Jessica Emonts, Angela Schmitz, Robert Heinrich Schmitt

0

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

5

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
A Riemannian Optimization Perspective of the Gauss-Newton Method for Feedforward Neural Networks
2024 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Semih Çaycı

6

citations
Portable to Efficient: Auto-Tuning Hardware-Agnostic GPU Kernels in Julia
2026 International Conference on Parallel Processing Workshops (ICPPW) conference-paper Computer Science Parallel Computing and Optimization Techniques Open access

Floris-Jan Willemsen, Evelyne Ringoot, Alan S. Edelman

0

citations