Meng Liu [刘猛]

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

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 Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji

Paper Code

DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding

Haitao Lin*, Yufei Huang*, Meng Liu, Xuanjing Li, Shuiwang Ji, and Stan Z. Li

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods

Montgomery Bohde*, Meng Liu*, Alexandra Saxton, Shuiwang Ji

International Conference on Learning Representations (ICLR), 2024

Spotlight

Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm

Meng Liu, Haiyang Yu, and Shuiwang Ji

Transactions on Machine Learning Research (TMLR), 2024

Paper Paper collection

Video Timeline Modeling for News Story Understanding

Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, and Boqing Gong

Advances in Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2023

Spotlight

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Haiyang Yu*, Meng Liu*, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, and Shuiwang Ji

Advances in Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2023

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, and Shuiwang Ji

Advances in Neural Information Processing Systems (NeurIPS), 2023

Graph Mixup with Soft Alignments

Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, and Na Zou

International Conference on Machine Learning (ICML), 2023

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

Meng Liu, Haoran Liu, and Shuiwang Ji

International Conference on Learning Representations (ICLR), 2023

Generating 3D Molecules for Target Protein Binding

Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, and Shuiwang Ji

International Conference on Machine Learning (ICML), 2022

Oral (2.1% acceptance rate)

Paper Code Video

GraphFM: Improving Large-Scale GNN Training via Feature Momentum

Haiyang Yu*, Limei Wang*, Bokun Wang*, Meng Liu, Tianbao Yang, and Shuiwang Ji

International Conference on Machine Learning (ICML), 2022

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery

Zhengyang Wang*, Meng Liu*, Youzhi Luo*, Zhao Xu*, Yaochen Xie*, Limei Wang*, Lei Cai*, Qi Qi, Zhuoning Yuan, Tianbao Yang, and Shuiwang Ji

Bioinformatics, 2022

Rank #1 on AI Cures open challenge for COVID-19

Paper Code Supplement

Spherical Message Passing for 3D Molecular Graphs

Yi Liu*, Limei Wang*, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, and Shuiwang Ji

International Conference on Learning Representations (ICLR), 2022

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences

Meng Liu and Shuiwang Ji

SIAM International Conference on Data Mining (SDM), 2022

Non-Local Graph Neural Networks

Meng Liu*, Zhengyang Wang*, and Shuiwang Ji

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

Paper Code Paper collection

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks

Meng Liu*, Cong Fu*, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, and Shuiwang Ji

AI4Science Workshop at NeurIPS, 2021

Awardee of KDD Cup 2021 on OGB-LSC

Paper Code

DIG: A Turnkey Library for Diving into Graph Deep Learning Research

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, and Shuiwang Ji

Journal of Machine Learning Research (JMLR), 2021

Join the DIG slack community!

Paper Code Documentation

GraphEBM: Molecular Graph Generation with Energy-Based Models

Meng Liu, Keqiang Yan, Bora Oztekin, and Shuiwang Ji

EBM Workshop at ICLR, 2021

Towards Deeper Graph Neural Networks

Meng Liu, Hongyang Gao, and Shuiwang Ji

ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020

Paper Code Paper collection