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ORCIDZaixi Zhang
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2020 – today
- 2024
[c18]Zhilin Huang, Ling Yang, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang:
Binding-Adaptive Diffusion Models for Structure-Based Drug Design. AAAI 2024: 12671-12679- [c17]Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen:
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. ICML 2024 - [c16]Jingyu Peng, Qi Liu, Linan Yue, Zaixi Zhang, Kai Zhang, Yunhao Sha:
Towards Few-Shot Self-explaining Graph Neural Networks. ECML/PKDD (6) 2024: 109-126 - [i24]Zaixi Zhang, Qingyong Hu, Yang Yu, Weibo Gao, Qi Liu:
FedGT: Federated Node Classification with Scalable Graph Transformer. CoRR abs/2401.15203 (2024) - [i23]Zhilin Huang, Ling Yang, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang:
Binding-Adaptive Diffusion Models for Structure-Based Drug Design. CoRR abs/2402.18583 (2024) - [i22]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:
Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation. CoRR abs/2404.00014 (2024) - [i21]Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen:
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. CoRR abs/2406.01977 (2024) - [i20]Kangyu Zheng, Yingzhou Lu, Zaixi Zhang, Zhongwei Wan, Yao Ma, Marinka Zitnik, Tianfan Fu:
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate? CoRR abs/2406.03403 (2024) - [i19]Ouxiang Li, Yanbin Hao, Zhicai Wang, Bin Zhu, Shuo Wang, Zaixi Zhang, Fuli Feng:
Model Inversion Attacks Through Target-Specific Conditional Diffusion Models. CoRR abs/2407.11424 (2024) - [i18]Jingyu Peng, Qi Liu, Linan Yue, Zaixi Zhang, Kai Zhang, Yunhao Sha:
Towards Few-shot Self-explaining Graph Neural Networks. CoRR abs/2408.07340 (2024) - 2023
- [j2]Zaixi Zhang
, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen:
Model Inversion Attacks Against Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(9): 8729-8741 (2023) - [c15]Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, Zaixi Zhang:
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense. AAAI 2023: 4854-4863 - [c14]Zaixi Zhang, Qi Liu, Zhicai Wang, Zepu Lu, Qingyong Hu:
Backdoor Defense via Deconfounded Representation Learning. CVPR 2023: 12228-12238 - [c13]Zaixi Zhang, Yaosen Min, Shuxin Zheng, Qi Liu:
Molecule Generation For Target Protein Binding with Structural Motifs. ICLR 2023 - [c12]Zaixi Zhang, Qi Liu:
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design. ICML 2023: 41382-41398 - [c11]Zepu Lu, Jin Chen, Defu Lian, Zaixi Zhang, Yong Ge, Enhong Chen:
Knowledge Distillation for High Dimensional Search Index. NeurIPS 2023 - [c10]Yang Yu, Qi Liu, Kai Zhang, Yuren Zhang, Chao Song, Min Hou, Yuqing Yuan, Zhihao Ye, Zaixi Zhang, Sanshi Lei Yu:
AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking. NeurIPS 2023 - [c9]Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu:
Full-Atom Protein Pocket Design via Iterative Refinement. NeurIPS 2023 - [c8]Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang, Neil Zhenqiang Gong:
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information. SP 2023: 1366-1383 - [c7]Zepu Lu, Defu Lian, Jin Zhang, Zaixi Zhang, Chao Feng, Hao Wang, Enhong Chen:
Differentiable Optimized Product Quantization and Beyond. WWW 2023: 3353-3363 - [i17]Zaixi Zhang, Qi Liu, Zhicai Wang, Zepu Lu, Qingyong Hu:
Backdoor Defense via Deconfounded Representation Learning. CoRR abs/2303.06818 (2023) - [i16]Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen:
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design. CoRR abs/2304.12436 (2023) - [i15]Zaixi Zhang, Qi Liu:
Learning Subpocket Prototypes for Generalizable Structure-based Drug Design. CoRR abs/2305.13997 (2023) - [i14]Zaixi Zhang, Jiaxian Yan, Qi Liu, Enhong Chen:
A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design. CoRR abs/2306.11768 (2023) - [i13]Yang Yu, Qi Liu, Kai Zhang, Yuren Zhang, Chao Song, Min Hou, Yuqing Yuan, Zhihao Ye, Zaixi Zhang, Sanshi Lei Yu:
AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking. CoRR abs/2310.09706 (2023) - [i12]Ziyang Xiang, Zaixi Zhang, Qi Liu:
Sparse Attention-Based Neural Networks for Code Classification. CoRR abs/2311.06575 (2023) - [i11]Jiaxian Yan, Zaixi Zhang, Kai Zhang, Qi Liu:
Multi-scale Iterative Refinement towards Robust and Versatile Molecular Docking. CoRR abs/2311.18574 (2023) - 2022
- [j1]Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia, Neil Zhenqiang Gong:
FLCert: Provably Secure Federated Learning Against Poisoning Attacks. IEEE Trans. Inf. Forensics Secur. 17: 3691-3705 (2022) - [c6]Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee:
ProtGNN: Towards Self-Explaining Graph Neural Networks. AAAI 2022: 9127-9135 - [c5]Zaixi Zhang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong:
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients. KDD 2022: 2545-2555 - [c4]Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee:
Hierarchical Graph Transformer with Adaptive Node Sampling. NeurIPS 2022 - [i10]Zaixi Zhang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong:
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients. CoRR abs/2207.09209 (2022) - [i9]Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen:
Model Inversion Attacks against Graph Neural Networks. CoRR abs/2209.07807 (2022) - [i8]Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia, Neil Zhenqiang Gong:
FLCert: Provably Secure Federated Learning against Poisoning Attacks. CoRR abs/2210.00584 (2022) - [i7]Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee:
Hierarchical Graph Transformer with Adaptive Node Sampling. CoRR abs/2210.03930 (2022) - [i6]Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang, Neil Zhenqiang Gong:
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information. CoRR abs/2210.10936 (2022) - [i5]Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, Zaixi Zhang:
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense. CoRR abs/2212.05399 (2022) - 2021
- [c3]Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen:
GraphMI: Extracting Private Graph Data from Graph Neural Networks. IJCAI 2021: 3749-3755 - [c2]Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee:
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction. NeurIPS 2021: 15870-15882 - [c1]Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Backdoor Attacks to Graph Neural Networks. SACMAT 2021: 15-26 - [i4]Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen:
GraphMI: Extracting Private Graph Data from Graph Neural Networks. CoRR abs/2106.02820 (2021) - [i3]Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee:
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction. CoRR abs/2110.00987 (2021) - [i2]Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee:
ProtGNN: Towards Self-Explaining Graph Neural Networks. CoRR abs/2112.00911 (2021) - 2020
- [i1]Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Backdoor Attacks to Graph Neural Networks. CoRR abs/2006.11165 (2020)
Coauthor Index
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