Towards Deeper Graph Neural Networks. - Meng Liu 015; Hongyang Gao; Shuiwang Ji (KDD, 2020)

MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery. - Zhengyang Wang; Meng Liu 015; Youzhi Luo; Zhao Xu 005; Yaochen Xie; Limei Wang; Lei Cai; Shuiwang Ji (CoRR, 2020)

GraphEBM: Molecular Graph Generation with Energy-Based Models. - Meng Liu 015; Keqiang Yan; Bora Oztekin; Shuiwang Ji (CoRR, 2021)

Spherical Message Passing for 3D Graph Networks. - Yi Liu 059; Limei Wang; Meng Liu 015; Xuan Zhang; Bora Oztekin; Shuiwang Ji (CoRR, 2021)

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks. - Meng Liu 015; Cong Fu 003; Xuan Zhang; Limei Wang; Yaochen Xie; Hao Yuan 001; Youzhi Luo; Zhao Xu 005; Shenglong Xu; Shuiwang Ji (CoRR, 2021)

Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs. - Zhao Xu 005; Youzhi Luo; Xuan Zhang; Xinyi Xu; Yaochen Xie; Meng Liu 015; Kaleb Dickerson; Cheng Deng; Maho Nakata; Shuiwang Ji (CoRR, 2021)

DIG: A Turnkey Library for Diving into Graph Deep Learning Research. - Meng Liu 015; Youzhi Luo; Limei Wang; Yaochen Xie; Hao Yuan 001; Shurui Gui; Haiyang Yu 005; Zhao Xu 005; Jingtun Zhang; Yi Liu 059; Keqiang Yan; Haoran Liu; et al. (J. Mach. Learn. Res., 2021)

Spherical Message Passing for 3D Molecular Graphs. - Yi Liu 059; Limei Wang; Meng Liu 015; Yuchao Lin; Xuan Zhang; Bora Oztekin; Shuiwang Ji (ICLR, 2022)

Generating 3D Molecules for Target Protein Binding. - Meng Liu 015; Youzhi Luo; Kanji Uchino; Koji Maruhashi; Shuiwang Ji (ICML, 2022)

GraphFM: Improving Large-Scale GNN Training via Feature Momentum. - Haiyang Yu 005; Limei Wang; Bokun Wang; Meng Liu 015; Tianbao Yang; Shuiwang Ji (ICML, 2022)

Frontiers of Graph Neural Networks with DIG. - Shuiwang Ji; Meng Liu 015; Yi Liu 059; Youzhi Luo; Limei Wang; Yaochen Xie; Zhao Xu 005; Haiyang Yu 005 (KDD, 2022)

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. - Meng Liu 015; Shuiwang Ji (SDM, 2022)

Advanced graph and sequence neural networks for molecular property prediction and drug discovery. - Zhengyang Wang; Meng Liu 015; Youzhi Luo; Zhao Xu 005; Yaochen Xie; Limei Wang; Lei Cai; Qi Qi 006; Zhuoning Yuan; Tianbao Yang; Shuiwang Ji (Bioinform., 2022)

Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks. - Meng Liu 015; Haiyang Yu 005; Shuiwang Ji (CoRR, 2022)

DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding. - Haitao Lin; Yufei Huang 002; Meng Liu 015; Xuanjing Li; Shuiwang Ji; Stan Z. Li (CoRR, 2022)

Non-Local Graph Neural Networks. - Meng Liu 015; Zhengyang Wang; Shuiwang Ji (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. - Meng Liu 015; Haoran Liu; Shuiwang Ji (ICLR, 2023)

Graph Mixup with Soft Alignments. - Hongyi Ling; Zhimeng Jiang; Meng Liu 015; Shuiwang Ji; Na Zou 001 (ICML, 2023)

Graph and Geometry Generative Modeling for Drug Discovery. - Minkai Xu; Meng Liu 015; Wengong Jin; Shuiwang Ji; Jure Leskovec; Stefano Ermon (KDD, 2023)

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. - Shurui Gui; Meng Liu 015; Xiner Li; Youzhi Luo; Shuiwang Ji (NeurIPS, 2023)

Video Timeline Modeling For News Story Understanding. - Meng Liu 015; Mingda Zhang; Jialu Liu; Hanjun Dai; Ming-Hsuan Yang 001; Shuiwang Ji; Zheyun Feng; Boqing Gong (NeurIPS, 2023)

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. - Haiyang Yu 005; Meng Liu 015; Youzhi Luo; Alex Strasser; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (NeurIPS, 2023)

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. - Montgomery Bohde; Meng Liu 015; Alexandra Saxton; Shuiwang Ji (ICLR, 2024)

Molecule Generation with Fragment Retrieval Augmentation. - Seul Lee; Karsten Kreis; Srimukh Prasad Veccham; Meng Liu 015; Danny Reidenbach; Saee Paliwal; Arash Vahdat; Weili Nie (NeurIPS, 2024)

3D Molecular Geometry Analysis with 2D Graphs. - Zhao Xu 005; Yaochen Xie; Youzhi Luo; Xuan Zhang; Xinyi Xu; Meng Liu 015; Kaleb Dickerson; Cheng Deng; Maho Nakata; Shuiwang Ji (SDM, 2024)

BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. - 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; et al. (CoRR, 2024)

Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm. - Meng Liu 015; Haiyang Yu 005; Shuiwang Ji (Trans. Mach. Learn. Res., 2024)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

GenMol: A Drug Discovery Generalist with Discrete Diffusion. - Seul Lee; Karsten Kreis; Srimukh Prasad Veccham; Meng Liu 015; Danny Reidenbach; Yuxing Peng 005; Saee Paliwal; Weili Nie; Arash Vahdat (CoRR, 2025)

ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha. - Meng Liu 015; 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; et al. (CoRR, 2025)