DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems
出版年份 2023 全文链接
标题
DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems
作者
关键词
-
出版物
IEEE Systems Journal
Volume 17, Issue 3, Pages 4360-4370
出版商
Institute of Electrical and Electronics Engineers (IEEE)
发表日期
2023-08-08
DOI
10.1109/jsyst.2023.3298884
参考文献
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- (2023) Christian Moya et al. NEUROCOMPUTING
- A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials
- (2022) Somdatta Goswami et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- A data-centric weak supervised learning for highway traffic incident detection
- (2022) Yixuan Sun et al. ACCIDENT ANALYSIS AND PREVENTION
- MIONet: Learning Multiple-Input Operators via Tensor Product
- (2022) Pengzhan Jin et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks
- (2021) Shengze Cai et al. JOURNAL OF COMPUTATIONAL PHYSICS
- A Comprehensive Survey on Graph Neural Networks
- (2020) Zonghan Wu et al. IEEE Transactions on Neural Networks and Learning Systems
- ConvPDE-UQ: Convolutional neural networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains
- (2019) Nick Winovich et al. JOURNAL OF COMPUTATIONAL PHYSICS
- Data driven governing equations approximation using deep neural networks
- (2019) Tong Qin et al. JOURNAL OF COMPUTATIONAL PHYSICS
- T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction
- (2019) Ling Zhao et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Robust data-driven discovery of governing physical laws with error bars
- (2018) Sheng Zhang et al. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
- Sparse identification of nonlinear dynamics for model predictive control in the low-data limit
- (2018) E. Kaiser et al. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
- Learning partial differential equations via data discovery and sparse optimization
- (2017) Hayden Schaeffer PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
- Discovering governing equations from data by sparse identification of nonlinear dynamical systems
- (2016) Steven L. Brunton et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Big data and its technical challenges
- (2014) H. V. Jagadish et al. COMMUNICATIONS OF THE ACM
- Wavelets on graphs via spectral graph theory
- (2010) David K. Hammond et al. APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS
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