Zaixi Zhang

According to our database, Zaixi Zhang authored at least 30 papers between 2021 and 2024.

Collaborative distances:

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

2024

FoldMark: Protecting Protein Generative Models with Watermarking.

Zaixi Zhang, Ruofan Jin, Kaidi Fu, Le Cong, Marinka Zitnik, Mengdi Wang

CoRR, 2024

DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking.

Jiaxian Yan, Zaixi Zhang, Jintao Zhu, Kai Zhang, Jianfeng Pei, Qi Liu

CoRR, 2024

Model Inversion Attacks Through Target-Specific Conditional Diffusion Models.

Ouxiang Li, Yanbin Hao, Zhicai Wang, Bin Zhu, Shuo Wang, Zaixi Zhang, Fuli Feng

CoRR, 2024

Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?

Kangyu Zheng, Yingzhou Lu, Zaixi Zhang, Zhongwei Wan, Yao Ma, Marinka Zitnik, Tianfan Fu

CoRR, 2024

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation.

Odin Zhang, Yufei Huang, Shichen Cheng, Mengyao Yu, Xujun Zhang, Haitao Lin, Yundian Zeng, Mingyang Wang, Zhenxing Wu, Huifeng Zhao, Zaixi Zhang, Chenqing Hua, Yu Kang, Sunliang Cui, Peichen Pan, Chang-Yu Hsieh, Tingjun Hou

CoRR, 2024

FedGT: Federated Node Classification with Scalable Graph Transformer.

Zaixi Zhang, Qingyong Hu, Yang Yu, Weibo Gao, Qi Liu

CoRR, 2024

Towards Few-Shot Self-explaining Graph Neural Networks.

Jingyu Peng, Qi Liu, Linan Yue, Zaixi Zhang, Kai Zhang, Yunhao Sha

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding.

Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Binding-Adaptive Diffusion Models for Structure-Based Drug Design.

Zhilin Huang, Ling Yang, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Model Inversion Attacks Against Graph Neural Networks.

Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen

IEEE Trans. Knowl. Data Eng., September, 2023

Multi-scale Iterative Refinement towards Robust and Versatile Molecular Docking.

Jiaxian Yan, Zaixi Zhang, Kai Zhang, Qi Liu

CoRR, 2023

Sparse Attention-Based Neural Networks for Code Classification.

Ziyang Xiang, Zaixi Zhang, Qi Liu

CoRR, 2023

A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design.

Zaixi Zhang, Jiaxian Yan, Qi Liu, Enhong Chen

CoRR, 2023

An Equivariant Generative Framework for Molecular Graph-Structure Co-Design.

Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen

CoRR, 2023

Differentiable Optimized Product Quantization and Beyond.

Zepu Lu, Defu Lian, Jin Zhang, Zaixi Zhang, Chao Feng, Hao Wang, Enhong Chen

Proceedings of the ACM Web Conference 2023, 2023

FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information.

Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang, Neil Zhenqiang Gong

Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Full-Atom Protein Pocket Design via Iterative Refinement.

Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking.

Yang Yu, Qi Liu, Kai Zhang, Yuren Zhang, Chao Song, Min Hou, Yuqing Yuan, Zhihao Ye, Zaixi Zhang, Sanshi Lei Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Knowledge Distillation for High Dimensional Search Index.

Zepu Lu, Jin Chen, Defu Lian, Zaixi Zhang, Yong Ge, Enhong Chen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Subpocket Prototypes for Generalizable Structure-based Drug Design.

Zaixi Zhang, Qi Liu

Proceedings of the International Conference on Machine Learning, 2023

Molecule Generation For Target Protein Binding with Structural Motifs.

Zaixi Zhang, Yaosen Min, Shuxin Zheng, Qi Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Backdoor Defense via Deconfounded Representation Learning.

Zaixi Zhang, Qi Liu, Zhicai Wang, Zepu Lu, Qingyong Hu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense.

Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, Zaixi Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

FLCert: Provably Secure Federated Learning Against Poisoning Attacks.

Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia, Neil Zhenqiang Gong

IEEE Trans. Inf. Forensics Secur., 2022

Hierarchical Graph Transformer with Adaptive Node Sampling.

Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients.

Zaixi Zhang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong

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

ProtGNN: Towards Self-Explaining Graph Neural Networks.

Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Backdoor Attacks to Graph Neural Networks.

Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong

Proceedings of the SACMAT '21: The 26th ACM Symposium on Access Control Models and Technologies, 2021

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction.

Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee

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

GraphMI: Extracting Private Graph Data from Graph Neural Networks.

Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021