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Papers matching “adaptive kernel” 17

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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
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
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
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
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
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
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
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
Fundamental Limitations of QAOA on Constrained Problems and a Route to Exponential Enhancement
2025 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Chinonso Onah, Kristel F. L. Michielsen

9

citations
Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free Approach
2023 arXiv (Cornell University) preprint Computer Science Domain Adaptation and Few-Shot Learning Open access

Sanaz Karimijafarbigloo, Reza Azad, Dorit Merhof

1

citations
SALTED: a symmetry-adapted machine-learning program for predicting electron-densities in molecules and materials
2026 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access

Zekun Lou, Alan M. Lewis, T. Bernhard, Lukas Seifert, Agustín Salcedo, Florian Kleemiss, +2 more

0

citations

17 results