Jonathan W. Siegel

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 27

Top Topics

Greedy Algorithm

Convergence Rate

Top Venues

IEEE Trans. Inf. Theory

J. Comput. Phys.

Found. Comput. Math.

Publications

Nadav Dym, Hannah Lawrence, Jonathan W. Siegel
Equivariant Frames and the Impossibility of Continuous Canonicalization. CoRR (2024)
Andrea Bonito, Ronald A. DeVore, Guergana Petrova, Jonathan W. Siegel
Convergence and error control of consistent PINNs for elliptic PDEs. CoRR (2024)
Jonathan W. Siegel
Sharp lower bounds on the manifold widths of Sobolev and Besov spaces. J. Complex. 85 (2024)
Jonathan W. Siegel
Sharp Lower Bounds on the Manifold Widths of Sobolev and Besov Spaces. CoRR (2024)
Jonathan W. Siegel, Jinchao Xu
Sharp Bounds on the Approximation Rates, Metric Entropy, and n-Widths of Shallow Neural Networks. Found. Comput. Math. 24 (2) (2024)
Kanan Gupta, Jonathan W. Siegel, Stephan Wojtowytsch
Achieving acceleration despite very noisy gradients. CoRR (2023)
Jonathan W. Siegel
Sharp Lower Bounds on Interpolation by Deep ReLU Neural Networks at Irregularly Spaced Data. CoRR (2023)
Yuwen Li, Jonathan W. Siegel
Entropy-based convergence rates of greedy algorithms. CoRR (2023)
Jonathan W. Siegel
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks. CoRR (2023)
Jonathan W. Siegel, Qingguo Hong, Xianlin Jin, Wenrui Hao, Jinchao Xu
Greedy training algorithms for neural networks and applications to PDEs. J. Comput. Phys. 484 (2023)
Jonathan W. Siegel, Stephan Wojtowytsch
A qualitative difference between gradient flows of convex functions in finite- and infinite-dimensional Hilbert spaces. CoRR (2023)
Jason M. Klusowski, Jonathan W. Siegel
Sharp Convergence Rates for Matching Pursuit. CoRR (2023)
Ronald DeVore, Robert D. Nowak, Rahul Parhi, Jonathan W. Siegel
Weighted variation spaces and approximation by shallow ReLU networks. CoRR (2023)
Qingguo Hong, Qinyang Tan, Jonathan W. Siegel, Jinchao Xu
On the Activation Function Dependence of the Spectral Bias of Neural Networks. CoRR (2022)
Jonathan W. Siegel, Jinchao Xu
Optimal Convergence Rates for the Orthogonal Greedy Algorithm. IEEE Trans. Inf. Theory 68 (5) (2022)
Jonathan W. Siegel
Optimal Approximation Rates for Deep ReLU Neural Networks on Sobolev Spaces. CoRR (2022)
Jonathan W. Siegel, Jinchao Xu
Sharp Lower Bounds on the Approximation Rate of Shallow Neural Networks. CoRR (2021)
Wenrui Hao, Xianlin Jin, Jonathan W. Siegel, Jinchao Xu
An efficient greedy training algorithm for neural networks and applications in PDEs. CoRR (2021)
Jonathan W. Siegel, Jinchao Xu
Optimal Approximation Rates and Metric Entropy of ReLU$^k$ and Cosine Networks. CoRR (2021)
Jonathan W. Siegel, Jinchao Xu
Characterization of the Variation Spaces Corresponding to Shallow Neural Networks. CoRR (2021)
Jonathan W. Siegel, Jinchao Xu
Improved Convergence Rates for the Orthogonal Greedy Algorithm. CoRR (2021)
Qingguo Hong, Jonathan W. Siegel, Jinchao Xu
Rademacher Complexity and Numerical Quadrature Analysis of Stable Neural Networks with Applications to Numerical PDEs. CoRR (2021)
Jonathan W. Siegel, Jinchao Xu
Activation Functions. CoRR (2020)
Jonathan W. Siegel, Jianhong Chen, Jinchao Xu
Training Sparse Neural Networks using Compressed Sensing. CoRR (2020)
Russel Caflisch, Hung Hsu Chou, Jonathan W. Siegel
Accuracy, Efficiency and Optimization of Signal Fragmentation. Multiscale Model. Simul. 18 (2) (2020)
Jonathan W. Siegel, Jinchao Xu
Approximation rates for neural networks with general activation functions. Neural Networks 128 (2020)
Jonathan W. Siegel, Jinchao Xu
On the Approximation Properties of Neural Networks. CoRR (2019)