Zaixi Zhang

Orcid: 0000-0002-0380-6558

According to our database1, Zaixi Zhang authored at least 24 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
FedGT: Federated Node Classification with Scalable Graph Transformer.
CoRR, 2024

Binding-Adaptive Diffusion Models for Structure-Based Drug Design.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Model Inversion Attacks Against Graph Neural Networks.
IEEE Trans. Knowl. Data Eng., September, 2023

Multi-scale Iterative Refinement towards Robust and Versatile Molecular Docking.
CoRR, 2023

Sparse Attention-Based Neural Networks for Code Classification.
CoRR, 2023

AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking.
CoRR, 2023

A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design.
CoRR, 2023

An Equivariant Generative Framework for Molecular Graph-Structure Co-Design.
CoRR, 2023

Differentiable Optimized Product Quantization and Beyond.
Proceedings of the ACM Web Conference 2023, 2023

FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Full-Atom Protein Pocket Design via Iterative Refinement.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

Molecule Generation For Target Protein Binding with Structural Motifs.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Backdoor Defense via Deconfounded Representation Learning.
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.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
FLCert: Provably Secure Federated Learning Against Poisoning Attacks.
IEEE Trans. Inf. Forensics Secur., 2022

Hierarchical Graph Transformer with Adaptive Node Sampling.
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.
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.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Backdoor Attacks to Graph Neural Networks.
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.
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.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021


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