E3: Towards energy-efficient distributed least squares estimation in sensor networks. - Wanyu Lin; Jiannong Cao 001; Xuefeng Liu 001 (IWQoS, 2014)

Multi-Client Searchable Encryption over Distributed Key-Value Stores. - Wanyu Lin; Xu Yuan 001; Baochun Li; Cong Wang 001 (SMARTCOMP, 2017)

Distributed Least Squares Estimation Algorithms Design for Sensor Networks. - Wanyu Lin; Jiannong Cao 001; Xuefeng Liu 001 (Ad Hoc Sens. Wirel. Networks, 2019)

Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data. - Wanyu Lin; Zhaolin Gao; Baochun Li (CoRR, 2019)

Adversarial Attacks on Link Prediction Algorithms Based on Graph Neural Networks. - Wanyu Lin; Shengxiang Ji; Baochun Li (AsiaCCS, 2020)

Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data. - Wanyu Lin; Zhaolin Gao; Baochun Li (CVPR, 2020)

Guardian: Evaluating Trust in Online Social Networks with Graph Convolutional Networks. - Wanyu Lin; Zhaolin Gao; Baochun Li (INFOCOM, 2020)

Hierarchical Deep Reinforcement Learning for Multi-robot Cooperation in Partially Observable Environment. - Zhixuan Liang; Jiannong Cao 001; Wanyu Lin; Jinlin Chen; Huafeng Xu (CogMI, 2021)

Generative Causal Explanations for Graph Neural Networks. - Wanyu Lin; Hao Lan; Baochun Li (ICML, 2021)

Medley: Predicting Social Trust in Time-Varying Online Social Networks. - Wanyu Lin; Baochun Li (INFOCOM, 2021)

Privacy-Preserving Similarity Search With Efficient Updates in Distributed Key-Value Stores. - Wanyu Lin; Helei Cui; Baochun Li; Cong Wang 001 (IEEE Trans. Parallel Distributed Syst., 2021)

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks. - Wanyu Lin; Hao Lan; Hao Wang 014; Baochun Li (CVPR, 2022)

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks. - Wanyu Lin; Hao Lan; Hao Wang 022; Baochun Li (CoRR, 2022)

1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct). - Hao Wang 014; Wanyu Lin; Hao He 011; Di Wang 015; Chengzhi Mao; Muhan Zhang (CoRR, 2022)

Towards Private Learning on Decentralized Graphs With Local Differential Privacy. - Wanyu Lin; Baochun Li; Cong Wang 001 (IEEE Trans. Inf. Forensics Secur., 2022)

Robust Graph Meta-Learning via Manifold Calibration with Proxy Subgraphs. - Zhenzhong Wang; Lulu Cao; Wanyu Lin; Min Jiang 005; Kay Chen Tan (AAAI, 2023)

SoftGPT: Learn Goal-Oriented Soft Object Manipulation Skills by Generative Pre-Trained Heterogeneous Graph Transformer. - Junjia Liu; Zhihao Li; Wanyu Lin; Sylvain Calinon; Kay Chen Tan; Fei Chen 007 (IROS, 2023)

SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency. - Cong Wang 018; Jinshan Pan; Wanyu Lin; Jiangxin Dong; Xiao-Ming Wu 003 (CoRR, 2023)

Practical Differentially Private and Byzantine-resilient Federated Learning. - Zihang Xiang; Tianhao Wang 001; Wanyu Lin; Di Wang 015 (Proc. ACM Manag. Data, 2023)

Prototype Correction via Contrastive Augmentation for Few-Shot Unconstrained Palmprint Recognition. - Kunlei Jing; Xinman Zhang; Chen Zhang 013; Wanyu Lin; Hebo Ma; Meng Pang; Bihan Wen (IEEE Trans. Inf. Forensics Secur., 2023)

A2S2-GNN: Rigging GNN-Based Social Status by Adversarial Attacks in Signed Social Networks. - Xiaoyan Yin 001; Wanyu Lin; Kexin Sun; Chun Wei; Yanjiao Chen (IEEE Trans. Inf. Forensics Secur., 2023)

Improving Accuracy and Convergence in Group-Based Federated Learning on Non-IID Data. - Ziqi He; Lei Yang 024; Wanyu Lin; Weigang Wu (IEEE Trans. Netw. Sci. Eng., 2023)

Personalized Federated Learning on Non-IID Data via Group-based Meta-learning. - Lei Yang 024; Jiaming Huang; Wanyu Lin; Jiannong Cao 001 (ACM Trans. Knowl. Discov. Data, 2023)

SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency. - Cong Wang 018; Jinshan Pan; Wanyu Lin; Jiangxin Dong; Wei Wang 335; Xiao-Ming Wu 003 (AAAI, 2024)

Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks. - Zhenzhong Wang; Qingyuan Zeng; Wanyu Lin; Min Jiang 005; Kay Chen Tan (AAAI, 2024)

Socialized Learning: Making Each Other Better Through Multi-Agent Collaboration. - Xinjie Yao; Yu Wang 106; Pengfei Zhu 001; Wanyu Lin; Jialu Li; Weihao Li; Qinghua Hu (ICML, 2024)

Explanations for Graph Neural Networks using A Game-theoretic Value. - Xueting Qiao; Wanyu Lin; Mingxuan Ouyang; Ting Jiang; Ji Zhang (IJCNN, 2024)

Adaptive Personalized Federated Learning for Non-IID Data with Continual Distribution Shift. - Sisi Chen; Weijie Liu; Xiaoxi Zhang 001; Hong Xu 001; Wanyu Lin; Xu Chen 004 (IWQoS, 2024)

What Matters in Graph Class Incremental Learning? An Information Preservation Perspective. - Jialu Li; Yu Wang 106; Pengfei Zhu 001; Wanyu Lin; Qinghua Hu (NeurIPS, 2024)

Diffusion-Driven Domain Adaptation for Generating 3D Molecules. - Haokai Hong; Wanyu Lin; Kay Chen Tan (CoRR, 2024)

Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data. - Zhenzhong Wang; Qingyuan Zeng; Wanyu Lin; Min Jiang 005; Kay Chen Tan (CoRR, 2024)

DPGAN: A Dual-Path Generative Adversarial Network for Missing Data Imputation in Graphs. - Xindi Zheng; Yuwei Wu; Yu Pan; Wanyu Lin; Lei Ma; Jianjun Zhao (CoRR, 2024)

Fast 3D Molecule Generation via Unified Geometric Optimal Transport. - Haokai Hong; Wanyu Lin; Kay Chen Tan (CoRR, 2024)

Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models. - Zhenzhong Wang; Zehui Lin; Wanyu Lin; Ming Yang; Minggang Zeng; Kay Chen Tan (CoRR, 2024)

Crystalline Material Discovery in the Era of Artificial Intelligence. - Zhenzhong Wang; Haowei Hua; Wanyu Lin; Ming Yang; Kay Chen Tan (CoRR, 2024)

Debiasing Graph Representation Learning based on Information Bottleneck. - Ziyi Zhang; Mingxuan Ouyang; Wanyu Lin; Hao Lan; Lei Yang (CoRR, 2024)

Fast Crystal Tensor Property Prediction: A General O(3)-Equivariant Framework Based on Polar Decomposition. - Haowei Hua; Wanyu Lin; Jingwen Yang (CoRR, 2024)

Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property Prediction. - Zhuoran Li; Xu Sun; Wanyu Lin; Jiannong Cao 001 (CoRR, 2024)

Accelerating AIGC Services with Latent Action Diffusion Scheduling in Edge Networks. - Changfu Xu; Jianxiong Guo; Wanyu Lin; Haodong Zou; Wentao Fan; Tian Wang 001; Xiaowen Chu 001; Jiannong Cao 001 (CoRR, 2024)

Status-Aware Signed Heterogeneous Network Embedding With Graph Neural Networks. - Wanyu Lin; Baochun Li (IEEE Trans. Neural Networks Learn. Syst., 2024)

Personalized Federated Learning with Layer-Wise Feature Transformation via Meta-Learning. - Jingke Tu; Jiaming Huang; Lei Yang 024; Wanyu Lin (ACM Trans. Knowl. Discov. Data, 2024)

Federated Class-Incremental Learning With Dynamic Feature Extractor Fusion. - Yanyan Lu; Lei Yang 024; Hao-Rui Chen; Jiannong Cao 001; Wanyu Lin; Saiqin Long (IEEE Trans. Mob. Comput., 2024)

A Physics-Informed Evolutionary Transfer Optimization Framework for Material Design. - Cheng Chen; Haokai Hong; Wanyu Lin; Kay Chen Tan (CEC, 2025)

Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport. - Haokai Hong; Wanyu Lin; Kc Tan (ICLR, 2025)

Visible-thermal cross-modality class-incremental learning. - Xinjie Yao; Yingxue Wang; Yu Wang 106; Pengfei Zhu 001; Ruipu Zhao; Weihao Li; Shenglei Pei; Wanyu Lin (Expert Syst. Appl., 2025)

Graph Privacy Funnel: A Variational Approach for Privacy-Preserving Representation Learning on Graphs. - Wanyu Lin; Hao Lan; Jiannong Cao 001 (IEEE Trans. Dependable Secur. Comput., 2025)

Graph-Relational Federated Learning: Enhanced Personalization and Robustness. - Wanyu Lin; Hao Lan; Hao He 011; Baochun Li (IEEE Trans. Dependable Secur. Comput., 2025)

Faithful Interpretation for Graph Neural Networks. - Lijie Hu; Tianhao Huang; Lu Yu; Wanyu Lin; Tianhang Zheng; Di Wang 015 (Trans. Mach. Learn. Res., 2025)

FedMUA: Exploring the Vulnerabilities of Federated Learning to Malicious Unlearning Attacks. - Jian Chen 046; Zehui Lin; Wanyu Lin; Wenlong Shi; Xiaoyan Yin; Di Wang (CoRR, 2025)

HPS: Hard Preference Sampling for Human Preference Alignment. - Xiandong Zou; Wanyu Lin; Yuchen Li; Pan Zhou (CoRR, 2025)

Local-Global Associative Frames for Symmetry-Preserving Crystal Structure Modeling. - Haowei Hua; Wanyu Lin (CoRR, 2025)

Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing. - Ye Du; Chen Yang; Nanxi Yu; Wanyu Lin; Qian Zhao; Shujun Wang (CoRR, 2025)

Knowledge Grafting of Large Language Models. - Guodong Du 002; Xuanning Zhou; Junlin Li; Zhuo Li; Zesheng Shi; Wanyu Lin; Ho-Kin Tang; Xiucheng Li; Fangming Liu; Wenya Wang; Min Zhang 005; Jing Li 034 (CoRR, 2025)

Boosting Pseudo-Labeling With Curriculum Self-Reflection for Attributed Graph Clustering. - Pengfei Zhu 001; Jialu Li; Yu Wang 106; Bin Xiao 002; Jinglin Zhang; Wanyu Lin; Qinghua Hu (IEEE Trans. Neural Networks Learn. Syst., 2025)

Understanding and Mitigating Cross-lingual Privacy Leakage via Language-specific and Universal Privacy Neurons. - Wenshuo Dong; Qingsong Yang; Shu Yang 010; Lijie Hu; Meng Ding; Wanyu Lin; Tianhang Zheng; Di Wang 015 (CoRR, 2025)

The Compositional Architecture of Regret in Large Language Models. - Xiangxiang Cui; Shu Yang 010; Tianjin Huang; Wanyu Lin; Lijie Hu; Di Wang 015 (CoRR, 2025)

Multiview Subgraph Neural Networks: Self-Supervised Learning With Scarce Labeled Data. - Zhenzhong Wang; Qingyuan Zeng; Wanyu Lin; Min Jiang 005; Kay Chen Tan (IEEE Trans. Neural Networks Learn. Syst., 2025)

Debiasing Graph Representation Learning Based on Information Bottleneck. - Ziyi Zhang; Mingxuan Ouyang; Wanyu Lin; Hao Lan; Lei Yang 024 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Multistage Graph Convolutional Network With Spatial Attention for Multivariate Time Series Imputation. - Qianyi Chen; Jiannong Cao 001; Yu Yang 012; Wanyu Lin; Sumei Wang; Youwu Wang (IEEE Trans. Neural Networks Learn. Syst., 2025)

Take Your Pick: Enabling Effective Distributed Learning Within Low-Dimensional Feature Space. - Guogang Zhu; Xuefeng Liu 001; Shaojie Tang 001; Jianwei Niu 002; Xinghao Wu; Jiaxing Shen; Wanyu Lin (IEEE Trans. Neural Networks Learn. Syst., 2025)