Jonathan W. Siegel
Scholar

Jonathan W. Siegel

Google Scholar ID: oI42qIIAAAAJ
Assistant Professor, Texas A&M University
Approximation TheoryStatisticsMachine Learning
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Citations & Impact
All-time
Citations
1,058
 
H-index
15
 
i10-index
19
 
Publications
20
 
Co-authors
18
list available
Contact
No contact links provided.
Publications
8 items
Quantitative Approximation Rates for Group Equivariant Learning
2026
Cited
0
In-Context Multi-Operator Learning with DeepOSets
2025
Cited
0
Nearly Optimal Bounds on the Fourier sampling numbers of Besov Spaces
2025
Cited
0
Optimal Recovery Meets Minimax Estimation
arXiv.org · 2025
Cited
1
On the expressiveness and spectral bias of KANs
arXiv.org · 2024
Cited
2
Approximation Rates for Shallow ReLU$^k$ Neural Networks on Sobolev Spaces via the Radon Transform
2024
Cited
4
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks
arXiv.org · 2023
Cited
6
Sharp Lower Bounds on Interpolation by Deep ReLU Neural Networks at Irregularly Spaced Data
arXiv.org · 2023
Cited
2
Resume (English only)
Co-authors
18 total
Jinchao Xu
Jinchao Xu
Professor of Applied Mathematics and Computational Sciences, KAUST
Co-author 2
Co-author 2
Wenrui Hao
Wenrui Hao
Professor of mathematics, Penn State University
Co-author 4
Co-author 4
Co-author 5
Co-author 5
Ronald DeVore
Ronald DeVore
Professor of Matematics, Texas A&M University
Stephan Wojtowytsch
Stephan Wojtowytsch
University of Pittsburgh
Rahul Parhi
Rahul Parhi
University of California, San Diego