[16] C Huang, L Zhao, JP Niu, JJ Di, JJ Yuan, QL Zhao, FQ Zhang, ZH Zhang, JM Lei, and GP He. Coupled particle and mesh method in an euler frame for unsteady flows around the pitching airfoil. Engineering Analysis with Boundary Elements, 138:159-176, 2022.
[17] Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, and Nitesh V Chawla. Online purchase prediction via multi-scale modeling of behavior dynamics. In KDD, pages 2613-2622, 2019.
[18] Zijie Huang, Yizhou Sun, and Wei Wang. Learning continuous system dynamics from irregularly-sampled partial observations. In NeurIPS, pages 16177-16187, 2020.
[19] Zijie Huang, Yizhou Sun, and Wei Wang. Coupled graph ode for learning interacting system dynamics. In KDD, 2021.
[20] Zijie Huang, Yizhou Sun, and Wei Wang. Generalizing graph ode for learning complex system dynamics across environments. In KDD, pages 798-809, 2023.
[21] Steeven Janny, Aurélien Beneteau, Nicolas Thome, Madiha Nadri, Julie Digne, and Christian Wolf. Eagle: Large-scale learning of turbulent fluid dynamics with mesh transformers. arXiv preprint arXiv:2302.10803, 2023.
[22] Hrivoje Jasak. Openfoam: open source cfd in research and industry. International Journal of Naval Architecture and Ocean Engineering, 1(2):89-94, 2009.
[23] Ruoxi Jiang and Rebecca Willett. Embed and emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. In NeurIPS, 2022.
[24] Patrick Kidger, Ricky T. Q. Chen, and Terry J. Lyons. "hey, that's not an ode": Faster ode adjoints via seminorms. ICML, 2021.
[25] Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, and Richard Zemel. Neural relational inference for interacting systems. In ICML, pages 2688-2697, 2018.
[26] Thomas N Kipf and Max Welling. Semi-supervised classification with graph convolutional networks. In ICLR, 2017.
[27] Miliadis Kofinas, Naveen Nagaraja, and Efstratios Gavves. Roto-translated local coordinate frames for interacting dynamical systems. In NeurIPS, 2021.
[28] Lingkai Kong, Jimeng Sun, and Chao Zhang. Sde-net: Equipping deep neural networks with uncertainty estimates. In ICML, 2020.
[29] Shiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, and Pyang Li. Dstagnn: Dynamic spatial-temporal aware graph neural network for traffic flow forecasting. In ICML, pages 11906-11917, 2022.
[30] Haoliang Li, Sinno Jialin Pan, Shiqi Wang, and Alex C Kot. Domain generalization with adversarial feature learning. In CVPR, pages 5400-5409, 2018.
[31] Haoliang Li, YuFei Wang, Renjie Wan, Shiqi Wang, Tie-Qiang Li, and Alex Kot. Domain generalization for medical imaging classification with linear-dependency regularization. In NeurIPS, pages 3118-3129, 2020.
[32] Haoyang Li, Ziwei Zhang, Xin Wang, and Wenwu Zhu. Learning invariant graph representations for out-of-distribution generalization. In NeurIPS, 2022.
[33] Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, and Weining Qian. Finding global homophily in graph neural networks when meeting heterophily. In ICML, pages 13242-13256, 2022.
[34] Xiaotong Li, Yongxing Dai, Yixiao Ge, Jun Liu, Ying Shan, and Ling-Yu Duan. Uncertainty modeling for out-of-distribution generalization. arXiv preprint arXiv:2202.03958, 2022.