On the influence of over-parameterization in manifold based surrogates and deep neural operators

9 March 2022

Papers citing "On the influence of over-parameterization in manifold based surrogates and deep neural operators"

25 / 25 papers shown

Title
Basis-to-Basis Operator Learning Using Function Encoders Tyler Ingebrand Adam J. Thorpe Somdatta Goswami Krishna Kumar Ufuk Topcu 21 3 0 30 Sep 2024
Efficient Training of Deep Neural Operator Networks via Randomized Sampling Sharmila Karumuri Lori Graham-Brady Somdatta Goswami 31 1 0 20 Sep 2024
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving Varun V. Kumar S. Goswami Katiana Kontolati Michael D. Shields George Em Karniadakis AI4CE 71 6 0 05 Aug 2024
Alternators For Sequence Modeling Mohammad Reza Rezaei Adji Bousso Dieng 28 0 0 20 May 2024
A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertainty Pratyush Kumar Singh Kathryn A. Farrell-Maupin D. Faghihi 40 6 0 13 Mar 2024
A novel Fourier neural operator framework for classification of multi-sized images: Application to three dimensional digital porous media Ali Kashefi T. Mukerji AI4CE 46 4 0 18 Feb 2024
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification Jungho Kim Sang-ri Yi Ziqi Wang 19 5 0 07 Feb 2024
Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification Dimitris G. Giovanis Dimitrios Loukrezis Ioannis G. Kevrekidis Michael D. Shields 33 3 0 30 Jan 2024
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 20 10 0 08 Oct 2023
DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks Katarzyna Michalowska S. Goswami George Karniadakis S. Riemer-Sørensen AI4TS 42 1 0 03 Oct 2023
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators N. Borrel-Jensen S. Goswami A. Engsig-Karup George Karniadakis C. Jeong AI4CE 41 16 0 09 Aug 2023
Learning in latent spaces improves the predictive accuracy of deep neural operators Katiana Kontolati S. Goswami George Karniadakis Michael D. Shields AI4CE 40 20 0 15 Apr 2023
LNO: Laplace Neural Operator for Solving Differential Equations Qianying Cao S. Goswami George Karniadakis 23 44 0 19 Mar 2023
Learning stiff chemical kinetics using extended deep neural operators S. Goswami Ameya Dilip Jagtap H. Babaee Bryan T. Susi George Karniadakis AI4CE 43 38 0 23 Feb 2023
Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils K. Shukla Vivek Oommen Ahmad Peyvan Michael Penwarden L. Bravo A. Ghoshal Robert M. Kirby George Karniadakis 33 19 0 02 Feb 2023
Physics-constrained 3D Convolutional Neural Networks for Electrodynamics A. Scheinker R. Pokharel 32 15 0 31 Jan 2023
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning Hrishikesh Viswanath Md Ashiqur Rahman Abhijeet Vyas Andrey Shor Beatriz Medeiros Stephanie Hernandez S. Prameela Aniket Bera PINN AI4CE 47 4 0 30 Jan 2023
A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling Qizhi He M. Perego Amanda A. Howard George Karniadakis P. Stinis 15 18 0 26 Jan 2023
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications Zhongkai Hao Songming Liu Yichi Zhang Chengyang Ying Yao Feng Hang Su Jun Zhu PINN AI4CE 37 91 0 15 Nov 2022
Physics-Informed Deep Neural Operator Networks S. Goswami Aniruddha Bora Yue Yu George Karniadakis PINN AI4CE 31 99 0 08 Jul 2022
SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability Simone Venturi T. Casey 23 37 0 27 Apr 2022
Deep transfer operator learning for partial differential equations under conditional shift S. Goswami Katiana Kontolati Michael D. Shields George Karniadakis 38 97 0 20 Apr 2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 30 40 0 09 Feb 2022
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 62 385 0 06 Nov 2021
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 256 2,298 0 18 Oct 2020