Samuel Lanthaler

According to our database, Samuel Lanthaler authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective.

Samuel Lanthaler

CoRR, 2024

Data Complexity Estimates for Operator Learning.

Nikola B. Kovachki, Samuel Lanthaler, Hrushikesh Mhaskar

CoRR, 2024

Discretization Error of Fourier Neural Operators.

Samuel Lanthaler, Andrew M. Stuart, Margaret Trautner

CoRR, 2024

Operator Learning: Algorithms and Analysis.

Nikola B. Kovachki, Samuel Lanthaler, Andrew M. Stuart

CoRR, 2024

2023

The curse of dimensionality in operator learning.

Samuel Lanthaler, Andrew M. Stuart

CoRR, 2023

The Nonlocal Neural Operator: Universal Approximation.

Samuel Lanthaler, Zongyi Li, Andrew M. Stuart

CoRR, 2023

Operator learning with PCA-Net: upper and lower complexity bounds.

Samuel Lanthaler

CoRR, 2023

Neural Oscillators are Universal.

Samuel Lanthaler, T. Konstantin Rusch, Siddhartha Mishra

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Error Bounds for Learning with Vector-Valued Random Features.

Samuel Lanthaler, Nicholas H. Nelsen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities.

Samuel Lanthaler, Roberto Molinaro, Patrik Hadorn, Siddhartha Mishra

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

On the approximation of functions by tanh neural networks.

Tim De Ryck, Samuel Lanthaler, Siddhartha Mishra

Neural Networks, 2021

On Universal Approximation and Error Bounds for Fourier Neural Operators.

Nikola B. Kovachki, Samuel Lanthaler, Siddhartha Mishra

J. Mach. Learn. Res., 2021

On the well-posedness of Bayesian inversion for PDEs with ill-posed forward problems.

Samuel Lanthaler, Siddhartha Mishra, Franziska Weber

CoRR, 2021

Error estimates for DeepOnets: A deep learning framework in infinite dimensions.

Samuel Lanthaler, Siddhartha Mishra, George Em Karniadakis

CoRR, 2021

2020

On the Convergence of the Spectral Viscosity Method for the Two-Dimensional Incompressible Euler Equations with Rough Initial Data.

Samuel Lanthaler, Siddhartha Mishra

Found. Comput. Math., 2020

On concentration in vortex sheets.

Samuel Lanthaler

CoRR, 2020

On the conservation of energy in two-dimensional incompressible flows.

Samuel Lanthaler, Siddhartha Mishra, Carlos Parés-Pulido

CoRR, 2020

2019

Statistical solutions of the incompressible Euler equations.

Samuel Lanthaler, Siddhartha Mishra, Carlos Parés-Pulido

CoRR, 2019