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

28 March 2023

Papers citing "Operator learning with PCA-Net: upper and lower complexity bounds"

19 / 19 papers shown

Title
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Julius Berner Miguel Liu-Schiaffini Jean Kossaifi Valentin Duruisseaux Boris Bonev Kamyar Azizzadenesheli A. Anandkumar AI4CE 127 0 0 12 Jun 2025
Learning Dual-Arm Coordination for Grasping Large Flat Objects Yongliang Wang Hamidreza Kasaei 95 2 0 04 Apr 2025
Theory-to-Practice Gap for Neural Networks and Neural Operators Philipp Grohs S. Lanthaler Margaret Trautner 117 3 0 23 Mar 2025
Neural Operators Can Play Dynamic Stackelberg Games Guillermo Alvarez Ibrahim Ekren Anastasis Kratsios Xuwei Yang 68 0 0 14 Nov 2024
DeepOSets: Non-Autoregressive In-Context Learning of Supervised Learning Operators Shao-Ting Chiu Junyuan Hong Ulisses Braga-Neto BDL 71 1 0 11 Oct 2024
Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations Takashi Furuya K. Taniguchi Satoshi Okuda 80 0 0 03 Oct 2024
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study Hao Liu Zecheng Zhang Wenjing Liao Hayden Schaeffer 73 1 0 01 Oct 2024
Operator Learning Using Random Features: A Tool for Scientific Computing Nicholas H. Nelsen Andrew M. Stuart 101 14 0 12 Aug 2024
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective Samuel Lanthaler 95 4 0 26 Jun 2024
Mixture of Experts Soften the Curse of Dimensionality in Operator Learning Anastasis Kratsios Takashi Furuya Jose Antonio Lara Benitez Matti Lassas Maarten V. de Hoop 90 14 0 13 Apr 2024
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 61 4 0 04 Apr 2024
Operator Learning: Algorithms and Analysis Nikola B. Kovachki S. Lanthaler Andrew M. Stuart 148 33 0 24 Feb 2024
A practical existence theorem for reduced order models based on convolutional autoencoders N. R. Franco Simone Brugiapaglia AI4CE 83 4 0 01 Feb 2024
Online Infinite-Dimensional Regression: Learning Linear Operators Vinod Raman Unique Subedi Ambuj Tewari 51 0 0 08 Sep 2023
Deep Operator Network Approximation Rates for Lipschitz Operators Ch. Schwab A. Stein Jakob Zech 60 10 0 19 Jul 2023
Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations Tengfei Xu Dachuan Liu Peng Hao Bo Wang 101 7 0 09 Apr 2023
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 92 35 0 06 Dec 2022
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis Luca Galimberti Anastasis Kratsios Giulia Livieri OOD 123 14 0 24 Oct 2022
Neural and spectral operator surrogates: unified construction and expression rate bounds L. Herrmann Christoph Schwab Jakob Zech 101 11 0 11 Jul 2022