Luo, Youzhi

16 publications

FnTML 2025 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, 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

ICML 2025 Geometry Informed Tokenization of Molecules for Language Model Generation Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji

AAAI 2025 Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation Haoran Liu, Youzhi Luo, Tianxiao Li, James Caverlee, Martin Renqiang Min

ICML 2024 Graph Structure Extrapolation for Out-of-Distribution Generalization Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji

ICLR 2023 Automated Data Augmentations for Graph Classification Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

ICML 2023 Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji

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

ICLR 2023 Learning Fair Graph Representations via Automated Data Augmentations Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou

NeurIPS 2023 QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

NeurIPS 2023 Towards Symmetry-Aware Generation of Periodic Materials Youzhi Luo, Chengkai Liu, Shuiwang Ji

ICLR 2022 An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch Youzhi Luo, Shuiwang Ji

ICML 2022 Generating 3D Molecules for Target Protein Binding Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

MLOSS 2021 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 M Oztekin, Xuan Zhang, Shuiwang Ji

NeurIPSW 2021 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, Shuiwang Ji

ICML 2021 GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo, Keqiang Yan, Shuiwang Ji

NeurIPS 2021 Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang