Samuel Lanthaler

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 23

Top Topics

Fourier Spectrum

Discretization Methods

Top Venues

Found. Comput. Math.

J. Mach. Learn. Res.

Publications

Nikola B. Kovachki, Samuel Lanthaler, Andrew M. Stuart
Operator Learning: Algorithms and Analysis. CoRR (2024)
Nikola B. Kovachki, Samuel Lanthaler, Hrushikesh Mhaskar
Data Complexity Estimates for Operator Learning. CoRR (2024)
Samuel Lanthaler, Andrew M. Stuart, Margaret Trautner
Discretization Error of Fourier Neural Operators. CoRR (2024)
Samuel Lanthaler
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective. CoRR (2024)
Samuel Lanthaler, Andrew M. Stuart
The curse of dimensionality in operator learning. CoRR (2023)
Samuel Lanthaler, Nicholas H. Nelsen
Error Bounds for Learning with Vector-Valued Random Features. CoRR (2023)
Samuel Lanthaler
Operator learning with PCA-Net: upper and lower complexity bounds. CoRR (2023)
Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities. ICLR (2023)
Samuel Lanthaler, T. Konstantin Rusch, Siddhartha Mishra
Neural Oscillators are Universal. NeurIPS (2023)
Samuel Lanthaler, Nicholas H. Nelsen
Error Bounds for Learning with Vector-Valued Random Features. NeurIPS (2023)
Samuel Lanthaler, Zongyi Li, Andrew M. Stuart
The Nonlocal Neural Operator: Universal Approximation. CoRR (2023)
Samuel Lanthaler, T. Konstantin Rusch, Siddhartha Mishra
Neural Oscillators are Universal. CoRR (2023)
Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities. CoRR (2022)
Nikola Kovachki, Samuel Lanthaler, Siddhartha Mishra
On universal approximation and error bounds for Fourier Neural Operators. CoRR (2021)
Tim De Ryck, Samuel Lanthaler, Siddhartha Mishra
On the approximation of functions by tanh neural networks. Neural Networks 143 (2021)
Tim De Ryck, Samuel Lanthaler, Siddhartha Mishra
On the approximation of functions by tanh neural networks. CoRR (2021)
Nikola Kovachki, Samuel Lanthaler, Siddhartha Mishra
On Universal Approximation and Error Bounds for Fourier Neural Operators. J. Mach. Learn. Res. 22 (2021)
Samuel Lanthaler, Siddhartha Mishra, George Em Karniadakis
Error estimates for DeepOnets: A deep learning framework in infinite dimensions. CoRR (2021)
Samuel Lanthaler, Siddhartha Mishra, Franziska Weber
On the well-posedness of Bayesian inversion for PDEs with ill-posed forward problems. CoRR (2021)
Samuel Lanthaler
On concentration in vortex sheets. CoRR (2020)
Samuel Lanthaler, Siddhartha Mishra, Carlos Parés-Pulido
On the conservation of energy in two-dimensional incompressible flows. CoRR (2020)
Samuel Lanthaler, Siddhartha Mishra
On the Convergence of the Spectral Viscosity Method for the Two-Dimensional Incompressible Euler Equations with Rough Initial Data. Found. Comput. Math. 20 (5) (2020)
Samuel Lanthaler, Siddhartha Mishra, Carlos Parés-Pulido
Statistical solutions of the incompressible Euler equations. CoRR (2019)