Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems:
Application to Monitoring Water Temperature And Quality In Lakes

Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes

5 October 2018

Anuj Karpatne

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Papers citing "Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes"

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Title
Physics-Infused Fuzzy Generative Adversarial Network for Robust Failure Prognosis Ryan D. Nguyen S. Singh Rahul Rai AI4CE 30 10 0 15 Jun 2022
Physics-Informed Deep Learning for Traffic State Estimation Rongye Shi Zhaobin Mo Kuang Huang Xuan Di Qi Du AI4TS 36 0 0 17 Jan 2021
Modeling Stochastic Microscopic Traffic Behaviors: a Physics Regularized Gaussian Process Approach Yun Yuan Qinzheng Wang X. Yang 67 10 0 17 Jul 2020
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE Juntang Zhuang Nicha Dvornek Xiaoxiao Li S. Tatikonda X. Papademetris James Duncan BDL 130 112 0 03 Jun 2020
Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales D. Feng K. Fang Chaopeng Shen AI4TS 103 282 0 18 Dec 2019
SNODE: Spectral Discretization of Neural ODEs for System Identification A. Quaglino Marco Gallieri Jonathan Masci Jan Koutník AI4TS 109 48 0 17 Jun 2019