Fu, Cong

12 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

ICLR 2025 Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models Cong Fu, Xiner Li, Blake Olson, Heng Ji, Shuiwang Ji

NeurIPS 2025 Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations Yuchao Lin, Cong Fu, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Kucukbenli, Xiaofeng Qian, Shuiwang Ji

ICLR 2024 Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

ICLR 2024 SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji

LoG 2023 A Latent Diffusion Model for Protein Structure Generation Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael Curtis McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji

ICML 2023 Group Equivariant Fourier Neural Operators for Partial Differential Equations Jacob Helwig, Xuan Zhang, Cong Fu, Jerry Kurtin, Stephan Wojtowytsch, Shuiwang Ji

LoG 2023 Semi-Supervised Learning for High-Fidelity Fluid Flow Reconstruction Cong Fu, Jacob Helwig, 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

IJCAI 2019 COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning Wenxiao Wang, Cong Fu, Jishun Guo, Deng Cai, Xiaofei He

IJCAI 2018 Translating Embeddings for Knowledge Graph Completion with Relation Attention Mechanism Wei Qian, Cong Fu, Yu Zhu, Deng Cai, Xiaofei He