Meng Liu - RankMe

48 papers A* 14A 2Journal 32

Year	Rank	Type	Title / Venue / Authors
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
2025	A*	`conf`	GenMol: A Drug Discovery Generalist with Discrete Diffusion. ICML Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Yuxing Peng, Saee Gopal Paliwal, Weili Nie, Arash Vahdat
2025	J	`jnl`	GenMol: A Drug Discovery Generalist with Discrete Diffusion. CoRR Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Yuxing Peng, Saee Paliwal, Weili Nie, Arash Vahdat
2025	J	`jnl`	Rethinking Molecule Synthesizability with Chain-of-Reaction. CoRR Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Weili Nie, Arash Vahdat
2025	J	`jnl`	ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha. CoRR Meng Liu, Karl Leswing, Simon K. S. Chu, Farhad Ramezanghorbani, Griffin Young, Gabriel Marques, Prerna Das, Anjali Panikar, Esther Jamir, Mohammed Sulaiman Shamsudeen, K. Shawn Watts, Ananya Sen, Hari Priya Devannagari, Edward B. Miller, Muyun Lihan, Howook Hwang, Janet Paulsen, Xin Yu, Kyle Gion, Timur Rvachov, Emine Küçükbenli, Saee Gopal Paliwal
2024	A	`conf`	3D Molecular Geometry Analysis with 2D Graphs. SDM Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji
2024	J	`jnl`	BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. CoRR Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick D. Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H. Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Saee Paliwal, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C. Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Küçükbenli, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B. Costa
2024	J	`jnl`	DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction. CoRR Meng Liu, Saee Gopal Paliwal
2024	J	`jnl`	Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm. Trans. Mach. Learn. Res. Meng Liu, Haiyang Yu, Shuiwang Ji
2024	A*	`conf`	Molecule Generation with Fragment Retrieval Augmentation. NeurIPS Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat, Weili Nie
2024	J	`jnl`	Molecule Generation with Fragment Retrieval Augmentation. CoRR Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat, Weili Nie
2024	A*	`conf`	On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. ICLR Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji
2024	J	`jnl`	On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. CoRR Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji
2023	J	`jnl`	3D Molecular Geometry Analysis with 2D Graphs. CoRR Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji
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`	Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. ICLR Meng Liu, Haoran Liu, Shuiwang Ji
2023	A*	`conf`	Graph Mixup with Soft Alignments. ICML Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou
2023	J	`jnl`	Graph Mixup with Soft Alignments. CoRR Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou
2023	A*	`conf`	Graph and Geometry Generative Modeling for Drug Discovery. KDD Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon
2023	A*	`conf`	Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. NeurIPS Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
2023	J	`jnl`	Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. CoRR Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
2023	A*	`conf`	QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. NeurIPS Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2023	J	`jnl`	QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. CoRR Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2023	A*	`conf`	Video Timeline Modeling For News Story Understanding. NeurIPS Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
2023	J	`jnl`	Video Timeline Modeling For News Story Understanding. CoRR Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
2022	J	`jnl`	Advanced graph and sequence neural networks for molecular property prediction and drug discovery. Bioinform. Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Qi Qi, Zhuoning Yuan, Tianbao Yang, Shuiwang Ji
2022	J	`jnl`	DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding. CoRR Haitao Lin, Yufei Huang, Meng Liu, Xuanjing Li, Shuiwang Ji, Stan Z. Li
2022	A*	`conf`	Frontiers of Graph Neural Networks with DIG. KDD Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu
2022	A*	`conf`	Generating 3D Molecules for Target Protein Binding. ICML Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji
2022	J	`jnl`	Generating 3D Molecules for Target Protein Binding. CoRR Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji
2022	J	`jnl`	Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. CoRR Meng Liu, Haoran Liu, Shuiwang Ji
2022	A*	`conf`	GraphFM: Improving Large-Scale GNN Training via Feature Momentum. ICML Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji
2022	J	`jnl`	GraphFM: Improving Large-Scale GNN Training via Feature Momentum. CoRR Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji
2022	A	`conf`	Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. SDM Meng Liu, Shuiwang Ji
2022	J	`jnl`	Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. CoRR Meng Liu, Shuiwang Ji
2022	J	`jnl`	Non-Local Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Meng Liu, Zhengyang Wang, Shuiwang Ji
2022	A*	`conf`	Spherical Message Passing for 3D Molecular Graphs. ICLR Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji
2022	J	`jnl`	Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks. CoRR Meng Liu, Haiyang Yu, Shuiwang Ji
2021	J	`jnl`	DIG: A Turnkey Library for Diving into Graph Deep Learning Research. CoRR Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Zhao Xu, Haiyang Yu, Jingtun Zhang, Yi Liu, Keqiang Yan, Bora Oztekin, Haoran Liu, Xuan Zhang, Cong Fu, Shuiwang Ji
2021	J	`jnl`	DIG: A Turnkey Library for Diving into Graph Deep Learning Research. J. Mach. Learn. Res. Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji
2021	J	`jnl`	Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks. CoRR Meng Liu, Cong Fu, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, Shuiwang Ji
2021	J	`jnl`	GraphEBM: Molecular Graph Generation with Energy-Based Models. CoRR Meng Liu, Keqiang Yan, Bora Oztekin, Shuiwang Ji
2021	J	`jnl`	Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs. CoRR Zhao Xu, Youzhi Luo, Xuan Zhang, Xinyi Xu, Yaochen Xie, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji
2021	J	`jnl`	Spherical Message Passing for 3D Graph Networks. CoRR Yi Liu, Limei Wang, Meng Liu, Xuan Zhang, Bora Oztekin, Shuiwang Ji
2020	J	`jnl`	MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery. CoRR Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Shuiwang Ji
2020	J	`jnl`	Non-Local Graph Neural Networks. CoRR Meng Liu, Zhengyang Wang, Shuiwang Ji
2020	A*	`conf`	Towards Deeper Graph Neural Networks. KDD Meng Liu, Hongyang Gao, Shuiwang Ji
2020	J	`jnl`	Towards Deeper Graph Neural Networks. CoRR Meng Liu, Hongyang Gao, Shuiwang Ji