Operator Learning of Lipschitz Operators: An Information-Theoretic
Perspective

Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective

26 June 2024

Samuel Lanthaler

Papers citing "Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective"

6 / 6 papers shown

Title
Theory-to-Practice Gap for Neural Networks and Neural Operators Philipp Grohs S. Lanthaler Margaret Trautner 36 1 0 23 Mar 2025
Simultaneously Solving FBSDEs with Neural Operators of Logarithmic Depth, Constant Width, and Sub-Linear Rank Takashi Furuya Anastasis Kratsios 30 1 0 18 Oct 2024
Operator Learning: Algorithms and Analysis Nikola B. Kovachki S. Lanthaler Andrew M. Stuart 46 22 0 24 Feb 2024
An operator learning perspective on parameter-to-observable maps Daniel Zhengyu Huang Nicholas H. Nelsen Margaret Trautner 32 11 0 08 Feb 2024
Variationally Mimetic Operator Networks Dhruv V. Patel Deep Ray M. Abdelmalik T. Hughes Assad A. Oberai 49 23 0 26 Sep 2022
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 208 2,287 0 18 Oct 2020