HybridNet: Integrating Model-based and Data-driven Learning to Predict
Evolution of Dynamical Systems

HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems

19 June 2018

Saibal Mukhopadhyay

Papers citing "HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems"

10 / 10 papers shown

Title
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 24 8 0 29 Dec 2023
Wave Physics-informed Matrix Factorizations Harsha Vardhan Tetali J. Harley B. Haeffele 27 0 0 21 Dec 2023
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 48 0 14 Nov 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 34 55 0 31 Mar 2022
Extension of Dynamic Mode Decomposition for dynamic systems with incomplete information based on t-model of optimal prediction Aleksandr Katrutsa S. Utyuzhnikov Ivan V. Oseledets 17 4 0 23 Feb 2022
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 25 152 0 09 Oct 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 37 64 0 02 Jul 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling Naoya Takeishi Alexandros Kalousis DRL AI4CE 22 54 0 25 Feb 2021
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting Yuan Yin Vincent Le Guen Jérémie Donà Emmanuel de Bézenac Ibrahim Ayed Nicolas Thome Patrick Gallinari AI4CE PINN 19 132 0 09 Oct 2020
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 227 7,903 0 13 Jun 2015