1. Inverse Design for Fluid-Structure Interactions using Graph Network Simulators;Allen Kelsey;Advances in Neural Information Processing Systems,2022
2. José E Andrade and Utkarsh Mital . 2019. Multiscale and Multiphysics Modeling of Soils . In Geotechnical Fundamentals for Addressing New World Challenges . Springer , 141–168. José E Andrade and Utkarsh Mital. 2019. Multiscale and Multiphysics Modeling of Soils. In Geotechnical Fundamentals for Addressing New World Challenges. Springer, 141–168.
3. Peter W Battaglia , Jessica B Hamrick , Victor Bapst , Alvaro Sanchez-Gonzalez , Vinicius Zambaldi , Mateusz Malinowski , Andrea Tacchetti , David Raposo , Adam Santoro , Ryan Faulkner , 2018. Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261 ( 2018 ). Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, 2018. Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261 (2018).
4. Yongjin Choi and Krishna Kumar . 2023. Graph Neural Network-based surrogate model for granular flows. arXiv preprint arXiv:2305.05218 ( 2023 ). Yongjin Choi and Krishna Kumar. 2023. Graph Neural Network-based surrogate model for granular flows. arXiv preprint arXiv:2305.05218 (2023).
5. Do E. 2019 . Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence. https://www.osti.gov/biblio/1478744 DoE. 2019. Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence. https://www.osti.gov/biblio/1478744