Rui Wang - RankMe

26 papers A* 7Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Physics-Guided Deep Learning for Dynamical Systems: A Survey. ACM Comput. Surv. Rui Wang, Rose Yu
2025	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Found. Trends Mach. Learn. Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2024	A*	`conf`	A Recipe for Charge Density Prediction. NeurIPS Xiang Fu, Andrew S. Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess E. Smidt, Tommi S. Jaakkola
2024	J	`jnl`	A Recipe for Charge Density Prediction. CoRR Xiang Fu, Andrew S. Rosen, Kyle Bystrom, Rui Wang, Albert Musaelian, Boris Kozinsky, Tess E. Smidt, Tommi S. Jaakkola
2024	A*	`conf`	Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution. ICML Rui Wang, Elyssa F. Hofgard, Hang Gao, Robin Walters, Tess E. Smidt
2024	J	`jnl`	Relaxed Equivariant Graph Neural Networks. CoRR Elyssa F. Hofgard, Rui Wang, Robin Walters, Tess E. Smidt
2024	J	`jnl`	Unsupervised social event detection via hybrid graph contrastive learning and reinforced incremental clustering. Knowl. Based Syst. Yuanyuan Guo, Zehua Zang, Hang Gao, Xiao Xu, Rui Wang, Lixiang Liu, Jiangmeng Li
2023	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
2023	A*	`conf`	Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts. ICLR Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu
2023	—	`—`	Physics-Guided Deep Learning for Dynamics Forecasting Rui Wang
2023	J	`jnl`	Relaxed Octahedral Group Convolution for Learning Symmetry Breaking in 3D Physical Systems. CoRR Rui Wang, Robin Walters, Tess E. Smidt
2023	J	`jnl`	Unsupervised Social Event Detection via Hybrid Graph Contrastive Learning and Reinforced Incremental Clustering. CoRR Yuanyuan Guo, Zehua Zang, Hang Gao, Xiao Xu, Rui Wang, Lixiang Liu, Jiangmeng Li
2022	A*	`conf`	Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. ICML Rui Wang, Robin Walters, Rose Yu
2022	J	`jnl`	Approximately Equivariant Networks for Imperfectly Symmetric Dynamics. CoRR Rui Wang, Robin Walters, Rose Yu
2022	J	`jnl`	Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting. CoRR Rui Wang, Robin Walters, Rose Yu
2022	J	`jnl`	Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts. CoRR Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu
2022	A*	`conf`	Meta-Learning Dynamics Forecasting Using Task Inference. NeurIPS Rui Wang, Robin Walters, Rose Yu
2021	—	`conf`	Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. L4DC Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu
2021	A*	`conf`	Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. ICLR Rui Wang, Robin Walters, Rose Yu
2021	J	`jnl`	Meta-Learning Dynamics Forecasting Using Task Inference. CoRR Rui Wang, Robin Walters, Rose Yu
2020	—	`conf`	Aortic Pressure Forecasting With Deep Learning. CinC Eliza Huang, Rui Wang, Uma Chandrasekaran, Rose Yu
2020	J	`jnl`	Aortic Pressure Forecasting with Deep Sequence Learning. CoRR Rui Wang, Eliza Huang, Uma Chandrasekaran, Rose Yu
2020	J	`jnl`	Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems. CoRR Rui Wang, Danielle C. Maddix, Christos Faloutsos, Yuyang Wang, Rose Yu
2020	J	`jnl`	Incorporating Symmetry into Deep Dynamics Models for Improved Generalization. CoRR Rui Wang, Robin Walters, Rose Yu
2020	A*	`conf`	Towards Physics-informed Deep Learning for Turbulent Flow Prediction. KDD Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu
2019	J	`jnl`	Towards Physics-informed Deep Learning for Turbulent Flow Prediction. CoRR Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu