NOMAD: Nonlinear Manifold Decoders for Operator Learning

7 June 2022

George J. Pappas

Papers citing "NOMAD: Nonlinear Manifold Decoders for Operator Learning"

48 / 48 papers shown

Title
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems Han Wan Rui Zhang Qi Wang Y. Liu Hao Sun PINN 35 0 0 03 May 2025
Towards scientific machine learning for granular material simulations -- challenges and opportunities Marc Fransen Andreas Fürst D. Tunuguntla Daniel N. Wilke Benedikt Alkin ... Takayuki Shuku WaiChing Sun T. Weinhart Dongwei Ye Hongyang Cheng AI4CE 29 0 0 01 Apr 2025
HyperNOs: Automated and Parallel Library for Neural Operators Research Massimiliano Ghiotto 46 0 0 23 Mar 2025
ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian Sensors Jake Rap Amritam Das 62 0 0 18 Mar 2025
On the Boundary Feasibility for PDE Control with Neural Operators Hanjiang Hu Changliu Liu AI4CE 64 1 0 23 Nov 2024
Generalizable Motion Planning via Operator Learning Sharath Matada Luke Bhan Yuanyuan Shi Nikolay Atanasov 23 0 0 23 Oct 2024
Score Neural Operator: A Generative Model for Learning and Generalizing Across Multiple Probability Distributions Xinyu Liao Aoyang Qin Jacob H. Seidman Junqi Wang Wei Wang P. Perdikaris DiffM 18 0 0 11 Oct 2024
Basis-to-Basis Operator Learning Using Function Encoders Tyler Ingebrand Adam J. Thorpe Somdatta Goswami Krishna Kumar Ufuk Topcu 11 3 0 30 Sep 2024
Micrometer: Micromechanics Transformer for Predicting Mechanical Responses of Heterogeneous Materials Sifan Wang Tong-Rui Liu Shyam Sankaran P. Perdikaris AI4CE 40 3 0 23 Sep 2024
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition Milad Ramezankhani Rishi Parekh A. Deodhar Dagnachew Birru AI4CE 29 0 0 13 Sep 2024
PinnDE: Physics-Informed Neural Networks for Solving Differential Equations Jason Matthews Alex Bihlo PINN 34 1 0 19 Aug 2024
Separable Operator Networks Xinling Yu S. Hooten Z. Liu Yequan Zhao M. Fiorentino T. Van Vaerenbergh Zheng-Wei Zhang 41 4 0 15 Jul 2024
Adaptive control of reaction-diffusion PDEs via neural operator-approximated gain kernels Luke Bhan Yuanyuan Shi Miroslav Krstic 38 4 0 01 Jul 2024
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study Milad Ramezankhani A. Deodhar Rishi Parekh Dagnachew Birru AI4CE 38 3 0 20 Jun 2024
FUSE: Fast Unified Simulation and Estimation for PDEs Levi E. Lingsch Dana Grund Siddhartha Mishra Georgios Kissas AI4CE 31 0 0 23 May 2024
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning Junfeng Chen Kailiang Wu 27 3 0 15 May 2024
MD-NOMAD: Mixture density nonlinear manifold decoder for emulating stochastic differential equations and uncertainty propagation Akshay Thakur Souvik Chakraborty 34 1 0 24 Apr 2024
Composite Bayesian Optimization In Function Spaces Using NEON -- Neural Epistemic Operator Networks Leonardo Ferreira Guilhoto P. Perdikaris BDL 25 1 0 03 Apr 2024
Operator Learning: Algorithms and Analysis Nikola B. Kovachki S. Lanthaler Andrew M. Stuart 36 22 0 24 Feb 2024
Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization Xiaoyu Xie S. Mowlavi M. Benosman AI4CE 27 1 0 23 Feb 2024
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators Benedikt Alkin Andreas Fürst Simon Schmid Lukas Gruber Markus Holzleitner Johannes Brandstetter PINN AI4CE 40 8 0 19 Feb 2024
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems Da Long Zhitong Xu Qiwei Yuan Yin Yang Shandian Zhe AI4CE 67 5 0 18 Feb 2024
Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning Jan-Philipp von Bassewitz Sebastian Kaltenbach P. Koumoutsakos AI4CE 30 1 0 01 Feb 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning Hao Liu Biraj Dahal Rongjie Lai Wenjing Liao AI4CE 21 5 0 19 Jan 2024
Generating synthetic data for neural operators Erisa Hasani Rachel A. Ward AI4CE 45 7 0 04 Jan 2024
HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork Jae Yong Lee S. Cho H. Hwang 23 22 0 26 Dec 2023
Deciphering and integrating invariants for neural operator learning with various physical mechanisms Rui Zhang Qi Meng Zhi-Ming Ma AI4CE 26 7 0 24 Nov 2023
Learning to Predict Structural Vibrations J. V. Delden Julius Schultz Christopher Blech Sabine C. Langer Timo Luddecke AI4CE 21 1 0 09 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 18 1 0 03 Oct 2023
Multi-Resolution Active Learning of Fourier Neural Operators Shibo Li Xin Yu Wei W. Xing Mike Kirby Akil Narayan Shandian Zhe AI4CE 25 4 0 29 Sep 2023
Learning Only On Boundaries: a Physics-Informed Neural operator for Solving Parametric Partial Differential Equations in Complex Geometries Z. Fang Sifan Wang P. Perdikaris AI4CE 17 11 0 24 Aug 2023
Understanding the Efficacy of U-Net & Vision Transformer for Groundwater Numerical Modelling M. L. Taccari O. Ovadia He-Nan Wang Adar Kahana Xiaohui Chen P. Jimack 32 2 0 08 Jul 2023
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning Francesca Bartolucci Emmanuel de Bezenac Bogdan Raonić Roberto Molinaro Siddhartha Mishra Rima Alaifari 21 27 0 31 May 2023
Generative Adversarial Reduced Order Modelling Dario Coscia N. Demo G. Rozza GAN AI4CE 34 5 0 25 May 2023
Nonlocality and Nonlinearity Implies Universality in Operator Learning S. Lanthaler Zong-Yi Li Andrew M. Stuart 16 16 0 26 Apr 2023
Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations Tengfei Xu Dachuan Liu Peng Hao Bo Wang 34 4 0 09 Apr 2023
Operator learning with PCA-Net: upper and lower complexity bounds S. Lanthaler 17 25 0 28 Mar 2023
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs Miroslav Krstic Luke Bhan Yuanyuan Shi 42 28 0 18 Mar 2023
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration Zhongyi Jiang Min Zhu Dongzhuo Li Qiuzi Li Yanhua O. Yuan Lu Lu AI4CE 46 49 0 08 Mar 2023
Variational Autoencoding Neural Operators Jacob H. Seidman Georgios Kissas George J. Pappas P. Perdikaris DRL AI4CE 25 7 0 20 Feb 2023
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation Rui Zhang Qi Meng Rongchan Zhu Yue Wang Wenlei Shi Shihua Zhang Zhi-Ming Ma Tie-Yan Liu DiffM AI4CE 44 4 0 10 Feb 2023
SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics P. Stinis C. Daskalakis P. Atzberger SyDa GAN 11 5 0 07 Feb 2023
Convolutional Neural Operators for robust and accurate learning of PDEs Bogdan Raonić Roberto Molinaro Tim De Ryck Tobias Rohner Francesca Bartolucci Rima Alaifari Siddhartha Mishra Emmanuel de Bezenac AAML 19 82 0 02 Feb 2023
Mitigating spectral bias for the multiscale operator learning Xinliang Liu Bo Xu Shuhao Cao Lei Zhang AI4CE 33 25 0 19 Oct 2022
Transformer Meets Boundary Value Inverse Problems Ruchi Guo Shuhao Cao Long Chen MedIm 28 20 0 29 Sep 2022
Improved architectures and training algorithms for deep operator networks Sifan Wang Hanwen Wang P. Perdikaris AI4CE 42 104 0 04 Oct 2021
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 124 200 0 28 Sep 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 203 2,281 0 18 Oct 2020