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Papers matching “Gaussian process limit” 9

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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
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
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 Optimization via Continual Variational Last Layer Training
2024 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek

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

3

citations
A theory of data variability in Neural Network Bayesian inference
2023 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias

0

citations
Graph Neural Networks Do Not Always Oversmooth
2024 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Bastian Epping, Alexandre René, Moritz Helias, Michael T. Schaub

3

citations
Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks
2025 arXiv (Cornell University) preprint Computer Science Advanced Multi-Objective Optimization Algorithms Open access

Shuaiqun Pan, Diederick Vermetten, Manuel López‐Ibáñez, Thomas Bäck, Hao Wang

2

citations
Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Bernd Frauenknecht, Lukas Kesper, Daniel Mayfrank, Henrik Hose, Sebastian Trimpe

0

citations

9 results