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Papers matching “Gaussian process limit” 24

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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
Global Optimization of Gaussian processes
2020 arXiv (Cornell University) preprint Mathematics Advanced Optimization Algorithms Research Open access

Artur M. Schweidtmann, Dominik Bongartz, Daniel Grothe, Tim Kerkenhoff, Xiaopeng Lin, Jaromił Najman, +1 more

5

citations
Characterizing Sparse Asteroid Light Curves with Gaussian Processes
2021 arXiv (Cornell University) preprint Physics and Astronomy Astro and Planetary Science Open access

Christina W. Lindberg, Daniela Huppenkothen, R. Lynne Jones, Bryce Bolin, Mario Jurić, Vahid Zachary Golkhou, +8 more

0

citations
A Functional Central Limit Theorem for Localized Partial Sums of Non-Stationary Time Series
2026 arXiv (Cornell University) preprint Mathematics Statistical Methods and Inference Open access

Florian Heinrichs

1

citations
A Functional Central Limit Theorem for Locally Stationary Time Series in Banach Spaces
2026 arXiv (Cornell University) preprint Mathematics Advanced Statistical Methods and Models Open access

Florian Heinrichs, Luis-Alberto Rodríguez

0

citations
Functional Central Limit Theorem for the simultaneous subgraph count of dynamic Erdős-Rényi random graphs
2025 arXiv (Cornell University) preprint Mathematics Limits and Structures in Graph Theory Open access

Rajat Subhra Hazra, Nikolai Kriukov, Michel Mandjes

0

citations
On the area between a Lévy process with secondary jump inputs and its reflected version
2023 arXiv (Cornell University) preprint Decision Sciences Probability and Risk Models Open access

Offer Kella, Michel Mandjes

0

citations
TransMEP: Transfer learning on large protein language models to predict mutation effects of proteins from a small known dataset
2024 bioRxiv (Cold Spring Harbor Laboratory) preprint Biochemistry, Genetics and Molecular Biology Machine Learning in Bioinformatics Open access

Tilman Hoffbauer, Birgit Strodel

7

citations
Euclid: Galaxy SED reconstruction in the PHZ processing function: impact on the PSF and the role of medium-band filters
2026 arXiv (Cornell University) preprint Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access

Euclid Collaboration, F. Tarsitano, C. Schreiber, Hironao Miyatake, Atsushi J. Nishizawa, Will G. Hartley, +94 more

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 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
Estimating Pore Location of PBF-LB/M Processes with Segmentation Models
2024 arXiv (Cornell University) preprint Engineering Additive Manufacturing Materials and Processes Open access

Hans Aoyang Zhou, Marco Kemmerling, Anas Abdelrazeq, Johannes Henrich Schleifenbaum, Robert Heinrich Schmitt

0

citations
Diagnosing the Fe line complex of the intracluster medium by XRISM high-resolution spectroscopy
2026 arXiv (Cornell University) preprint Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access

K. Fukushima, L. Hirata, N.Y. Yamasaki, Priyanka Chakraborty, S. Dupourqué, Y. Fujita, +14 more

0

citations
Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do?
2025 arXiv (Cornell University) preprint Decision Sciences Advanced Bandit Algorithms Research Open access

Anastasia Georgiou, Daniel Jungen, Luise F. Kaven, Verena Hunstig, Constantine Frangakis, Ioannis G. Kevrekidis, +1 more

4

citations
A Three-Dimensional Tomographic Reconstruction of the Galactic Cosmic-Ray Proton Density
2026 arXiv (Cornell University) preprint Physics and Astronomy Astrophysics and Cosmic Phenomena Open access

Hanieh Zandinejad, Jakob Roth, Vo Hong Minh Phan, Gordian Edenhofer, Philipp Mertsch, R. Kissmann, +3 more

1

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
Generating Synthetic Procurement Data for Small- And Medium-Sized Enterprises Using a Zero-Inflated Conditional Variational Autoencoder
2026 Research Square preprint Decision Sciences Supply Chain and Inventory Management Open access

Julian Stang, Jannik Stoever, Daniel Schnitzler, Jan Joppien, Marc Wegmann, Christina Reuter

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
MALLORN: Many Artificial LSST Lightcurves based on Observations of Real Nuclear transients
2025 arXiv (Cornell University) preprint Physics and Astronomy Gamma-ray bursts and supernovae Open access

0

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
MALLORN: Many Artificial LSST Lightcurves based on Observations of Real Nuclear transients
2025 arXiv (Cornell University) preprint Physics and Astronomy Gamma-ray bursts and supernovae Open access

Shubham Srivastav

0

citations

24 results