Zhao Xu

According to our database, Zhao Xu authored at least 14 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Self-Supervised Learning of Graph Neural Networks: A Unified Review.

Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhengyang Wang, Shuiwang Ji

IEEE Trans. Pattern Anal. Mach. Intell., 2023

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 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

CoRR, 2023

3D Molecular Geometry Analysis with 2D Graphs.

Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji

CoRR, 2023

A Text-guided Protein Design Framework.

Shengchao Liu, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Anthony Gitter, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar

CoRR, 2023

Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian.

Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

Proceedings of the International Conference on Machine Learning, 2023

2022

Frontiers of Graph Neural Networks with DIG.

Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Self-Supervised Representation Learning via Latent Graph Prediction.

Yaochen Xie, Zhao Xu, Shuiwang Ji

Proceedings of the International Conference on Machine Learning, 2022

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 Oztekin, Xuan Zhang, Shuiwang Ji

J. Mach. Learn. Res., 2021

Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs.

Zhao Xu, Youzhi Luo, Xuan Zhang, Xinyi Xu, Yaochen Xie, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji

CoRR, 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

CoRR, 2021

Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence.

Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang

CoRR, 2021

Self-Supervised Learning of Graph Neural Networks: A Unified Review.

Yaochen Xie, Zhao Xu, Zhengyang Wang, Shuiwang Ji

CoRR, 2021

Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence.

Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery.

Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Shuiwang Ji

CoRR, 2020