Inference of Infrastructure Network Flows via Physics-Inspired Implicit Neural Networks
Author:
Affiliation:
1. University of California,Center for Control, Dynamical Systems, and Computation,Santa Barbara
2. University of California,Department of Computer Science,Santa Barbara
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10252164/10252092/10252477.pdf?arnumber=10252477
Reference26 articles.
1. Physics-Informed Implicit Representations of Equilibrium Network Flows;smith;Advances in neural information processing systems,2022
2. Combining Physics and Machine Learning for Network Flow Estimation;silva,0
3. OptNet: Differentiable Optimization as a Layer in Neural Networks;amos,0
4. Graph-based Semi-Supervised & Active Learning for Edge Flows
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Identifying Edge Changes in Networks From Input and Output Covariance Data;IEEE Control Systems Letters;2024
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