Wei Jin - RankMe

126 papers A* 30A 9B 1Journal 72Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ECG-MoE: Mixture-of-Expert Electrocardiogram Foundation Model. CoRR Yuhao Xu, Xiaoda Wang, Yi Wu, Wei Jin, Xiao Hu, Carl Yang
2026	J	`jnl`	EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering for Enhanced Alignment and Reasoning. CoRR Mingyang Wei, Dehai Min, Zewen Liu, Yuzhang Xie, Guanchen Wu, Carl Yang, Max S. Y. Lau, Qi He, Lu Cheng, Wei Jin
2026	J	`jnl`	Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks. CoRR Bohan Wang, Zewen Liu, Lu Lin, Hui Liu, Li Xiong, Ming Jin, Wei Jin
2026	J	`jnl`	Patient-Conditioned Adaptive Offsets for Reliable Diagnosis across Subgroups. CoRR Gelei Xu, Yuying Duan, Jun Xia, Ruining Deng, Wei Jin, Yiyu Shi
2026	J	`jnl`	Rethinking fairness in medical imaging: Maximizing group-specific performance with application to skin disease diagnosis. Medical Image Anal. Gelei Xu, Yuying Duan, Jun Xia, Ching-Hao Chiu, Michael Lemmon, Wei Jin, Yiyu Shi
2026	J	`jnl`	STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement Learning. CoRR Juntong Ni, Shiyu Wang, Ming Jin, Qi He, Wei Jin
2026	—	`conf`	Scalable Graph Condensation with Evolving Capabilities. KDD (1) Shengbo Gong, Mohammad Hashemi, Juntong Ni, Carl Yang, Wei Jin
2026	—	`conf`	TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation. KDD (1) Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin
2025	J	`jnl`	A Unified AI Approach for Continuous Monitoring of Human Health and Diseases from Intensive Care Unit to Home with Physiological Foundation Models (UNIPHY+). CoRR Minxiao Wang, Saurabh Kataria, Juntong Ni, Timothy G. Buchman, Jocelyn Grunwell, Mark Mai, Wei Jin, Matthew Clark, Stephanie R. Brown, Michael Fundora, Puneet Sharma, Tony Pan, Sam Khan, Timothy Ruchti, Naveen Muthu, Kevin Maher, Sivasubramanium V. Bhavani, Xiao Hu
2025	—	`conf`	ADEPT-SQL: A High-performance Text-to-SQL Application for Real-World Enterprise-Level Databases. ACL (3) Yongnan Chen, Zhuo Chang, Shijia Gu, Yuanhang Zong, Mei Zhang, Shiyu Wang, Zixiang He, Hongzhi Chen, Wei Jin, Bin Cui
2025	J	`jnl`	An Adaptive Machine Learning Triage Framework for Predicting Alzheimer's Disease Progression. CoRR Richard Hou, Shengpu Tang, Wei Jin
2025	J	`jnl`	Are We Overlooking the Dimensions? Learning Latent Hierarchical Channel Structure for High-Dimensional Time Series Forecasting. CoRR Juntong Ni, Shiyu Wang, Zewen Liu, Xiaoming Shi, Xinyue Zhong, Zhou Ye, Wei Jin
2025	J	`jnl`	Beyond Chunks and Graphs: Retrieval-Augmented Generation through Triplet-Driven Thinking. CoRR Shengbo Gong, Xianfeng Tang, Carl Yang, Wei Jin
2025	J	`jnl`	CAPE: Covariate-Adjusted Pre-Training for Epidemic Time Series Forecasting. CoRR Zewen Liu, Juntong Ni, Max S. Y. Lau, Wei Jin
2025	J	`jnl`	Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series? CoRR Zewen Liu, Juntong Ni, Xianfeng Tang, Max S. Y. Lau, Wenpeng Yin, Wei Jin
2025	A*	`conf`	EARTH: Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph. ICML Guancheng Wan, Zewen Liu, Xiaojun Shan, Max S. Y. Lau, B. Aditya Prakash, Wei Jin
2025	—	`conf`	Efficient Epidemic Intervention Generation: A Graph Adversarial Attack Perspective. WWW (Companion Volume) Yunxiao Li, Mingyang Wei, Zewen Liu, Max S. Y. Lau, Wei Jin
2025	A	`conf`	Enabling Memory-Efficient On-Device Learning via Dataset Condensation. DATE Gelei Xu, Ningzhi Tang, Jun Xia, Ruiyang Qin, Wei Jin, Yiyu Shi
2025	—	`conf`	Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation. IJCNLP-AACL (long papers) Juanhui Li, Haoyu Han, Zhikai Chen, Harry Shomer, Wei Jin, Amin Javari, Hui Liu
2025	J	`jnl`	Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals. CoRR Saurabh Kataria, Yi Wu, Zhaoliang Chen, Gloria Hyunjung Kwak, Yuhao Xu, Lovely Yeswanth Panchumarthi, Ran Xiao, Jiaying Lu, Ayca Ermis, Anni Zhao, Runze Yan, Alex Federov, Zewen Liu, Xu Wu, Wei Jin, Carl Yang, Jocelyn Grunwell, Stephanie R. Brown, Amit J. Shah, Craig S. Jabaley, Timothy G. Buchman, Sivasubramanium V. Bhavani, Randall J. Lee, Xiao Hu
2025	—	`conf`	Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks. KDD (2) Zewen Liu, Xiaoda Wang, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin
2025	J	`jnl`	Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks. CoRR Zewen Liu, Xiaoda Wang, Bohan Wang, Zijie Huang, Carl Yang, Wei Jin
2025	J	`jnl`	Higher-order Interaction Matters: Dynamic Hypergraph Neural Networks for Epidemic Modeling. CoRR Songyuan Liu, Shengbo Gong, Tianning Feng, Zewen Liu, Max S. Y. Lau, Wei Jin
2025	J	`jnl`	Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Expert. CoRR Gelei Xu, Yuying Duan, Zheyuan Liu, Xueyang Li, Meng Jiang, Michael Lemmon, Wei Jin, Yiyu Shi
2025	—	`conf`	Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Experts. MICCAI (14) Gelei Xu, Yuying Duan, Zheyuan Liu, Xueyang Li, Meng Jiang, Michael Lemmon, Wei Jin, Yiyu Shi
2025	J	`jnl`	PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation. CoRR Juntong Ni, Saurabh Kataria, Shengpu Tang, Carl Yang, Xiao Hu, Wei Jin
2025	A*	`conf`	Precedence-Constrained Winter Value for Effective Graph Data Valuation. ICLR Hongliang Chi, Wei Jin, Charu C. Aggarwal, Yao Ma
2025	J	`jnl`	Scalable Graph Condensation with Evolving Capabilities. CoRR Shengbo Gong, Mohammad Hashemi, Juntong Ni, Carl Yang, Wei Jin
2025	—	`conf`	SciSoc LLM Workshop: Large Language Models for Scientific and Societal Advances. KDD (2) Wei Jin, Lu Cheng, Wenpeng Yin, Xianfeng Tang, Qingsong Wen, Danai Koutra, B. Aditya Prakash, Yan Liu
2025	—	`conf`	Time Series Analysis in the Web: Recent Advances and Future Trends. WWW (Companion Volume) Ming Jin, Wei Jin, Hao Xue, Flora Salim, Yuxuan Liang
2025	J	`jnl`	TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation. CoRR Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin
2025	J	`jnl`	TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness. CoRR Zhiyuan Zhao, Juntong Ni, Shangqing Xu, Haoxin Liu, Wei Jin, B. Aditya Prakash
2024	A*	`conf`	A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. IJCAI Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin
2024	J	`jnl`	A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. CoRR Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin
2024	—	`conf`	A Pure Transformer Pretraining Framework on Text-Attributed Graphs. LoG Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
2024	J	`jnl`	A Pure Transformer Pretraining Framework on Text-attributed Graphs. CoRR Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
2024	A*	`conf`	A Review of Graph Neural Networks in Epidemic Modeling. KDD Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
2024	J	`jnl`	A Review of Graph Neural Networks in Epidemic Modeling. CoRR Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
2024	A*	`conf`	CellPLM: Pre-training of Cell Language Model Beyond Single Cells. ICLR Hongzhi Wen, Wenzhuo Tang, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
2024	—	`conf`	DCAI: Data-centric Artificial Intelligence. WWW (Companion Volume) Wei Jin, Haohan Wang, Daochen Zha, Qiaoyu Tan, Yao Ma, Sharon Li, Su-In Lee
2024	J	`jnl`	Deep Learning in Single-cell Analysis. ACM Trans. Intell. Syst. Technol. Dylan Molho, Jiayuan Ding, Wenzhuo Tang, Zhaoheng Li, Hongzhi Wen, Yixin Wang, Julian Venegas, Wei Jin, Renming Liu, Runze Su, Patrick Danaher, Robert Yang, Yu Leo Lei, Yuying Xie, Jiliang Tang
2024	J	`jnl`	Enabling On-Device Learning via Experience Replay with Efficient Dataset Condensation. CoRR Gelei Xu, Ningzhi Tang, Jun Xia, Wei Jin, Yiyu Shi
2024	J	`jnl`	Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation. CoRR Juanhui Li, Haoyu Han, Zhikai Chen, Harry Shomer, Wei Jin, Amin Javari, Jiliang Tang
2024	J	`jnl`	EpiLearn: A Python Library for Machine Learning in Epidemic Modeling. CoRR Zewen Liu, Yunxiao Li, Mingyang Wei, Guancheng Wan, Max S. Y. Lau, Wei Jin
2024	J	`jnl`	Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph. CoRR Guancheng Wan, Zewen Liu, Max S. Y. Lau, B. Aditya Prakash, Wei Jin
2024	J	`jnl`	GC-Bench: A Benchmark Framework for Graph Condensation with New Insights. CoRR Shengbo Gong, Juntong Ni, Noveen Sachdeva, Carl Yang, Wei Jin
2024	A*	`conf`	Globally Interpretable Graph Learning via Distribution Matching. WWW Yi Nian, Yurui Chang, Wei Jin, Lu Lin
2024	A*	`conf`	Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. KDD Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
2024	J	`jnl`	Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. CoRR Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang
2024	—	`conf`	Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. ACL (Findings) Ran Xu, Hejie Cui, Yue Yu, Xuan Kan, Wenqi Shi, Yuchen Zhuang, May Dongmei Wang, Wei Jin, Joyce C. Ho, Carl Yang
2024	A*	`conf`	Label-free Node Classification on Graphs with Large Language Models (LLMs). ICLR Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
2024	J	`jnl`	Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness. CoRR Kai Guo, Zewen Liu, Zhikai Chen, Hongzhi Wen, Wei Jin, Jiliang Tang, Yi Chang
2024	A*	`conf`	Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching. ICML Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, Yang You
2024	J	`jnl`	Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching. CoRR Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, Yang You
2024	J	`jnl`	Precedence-Constrained Winter Value for Effective Graph Data Valuation. CoRR Hongliang Chi, Wei Jin, Charu Aggarwal, Yao Ma
2024	J	`jnl`	SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology. J. Comput. Biol. Jiayuan Ding, Lingxiao Li, Qiaolin Lu, Julian Venegas, Yixin Wang, Lidan Wu, Wei Jin, Hongzhi Wen, Renming Liu, Wenzhuo Tang, Xinnan Dai, Zhaoheng Li, Wangyang Zuo, Yi Chang, Yu Leo Lei, Lulu Shang, Patrick Danaher, Yuying Xie, Jiliang Tang
2024	A	`conf`	Spectral-Aware Augmentation for Enhanced Graph Representation Learning. CIKM Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu
2024	—	`conf`	Sub-Graph Based Diffusion Model for Link Prediction. LoG Hang Li, Wei Jin, Geri Skenderi, Harry Shomer, Wenzhuo Tang, Wenqi Fan, Jiliang Tang
2024	J	`jnl`	Sub-graph Based Diffusion Model for Link Prediction. CoRR Hang Li, Wei Jin, Geri Skenderi, Harry Shomer, Wenzhuo Tang, Wenqi Fan, Jiliang Tang
2024	A*	`conf`	Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. NeurIPS Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
2024	J	`jnl`	Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. CoRR Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
2024	A	`conf`	Trustworthy and Responsible AI for Information and Knowledge Management System. CIKM Huaming Chen, Jun Zhuang, Yu Yao, Wei Jin, Haohan Wang, Yong Xie, Chi-Hung Chi, Kim-Kwang Raymond Choo
2023	A*	`conf`	Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
2023	J	`jnl`	Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
2023	J	`jnl`	Augment with Care: Enhancing Graph Contrastive Learning with Selective Spectrum Perturbation. CoRR Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu
2023	J	`jnl`	Customized Graph Nerual Networks. IEEE Data Eng. Bull. Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang
2023	A*	`conf`	Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2023	J	`jnl`	Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? CoRR Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2023	A*	`conf`	Empowering Graph Representation Learning with Test-Time Graph Transformation. ICLR Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
2023	A*	`conf`	Enhancing Graph Representations Learning with Decorrelated Propagation. KDD Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu
2023	J	`jnl`	Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs. CoRR Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
2023	J	`jnl`	Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs. SIGKDD Explor. Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
2023	J	`jnl`	Graph Data Augmentation for Graph Machine Learning: A Survey. IEEE Data Eng. Bull. Tong Zhao, Wei Jin, Yozen Liu, Yingheng Wang, Gang Liu, Stephan Günnemann, Neil Shah, Meng Jiang
2023	J	`jnl`	INS-GNN: Improving graph imbalance learning with self-supervision. Inf. Sci. Xin Juan, Fengfeng Zhou, Wentao Wang, Wei Jin, Jiliang Tang, Xin Wang
2023	A*	`conf`	Jointly Attacking Graph Neural Network and its Explanations. ICDE Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
2023	J	`jnl`	Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. CoRR Ran Xu, Hejie Cui, Yue Yu, Xuan Kan, Wenqi Shi, Yuchen Zhuang, Wei Jin, Joyce C. Ho, Carl Yang
2023	J	`jnl`	Label-free Node Classification on Graphs with Large Language Models (LLMS). CoRR Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
2023	B	`conf`	Learning Representations for Hyper-Relational Knowledge Graphs. ASONAM Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu
2023	J	`jnl`	Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation. CoRR Hongzhi Wen, Wenzhuo Tang, Wei Jin, Jiayuan Ding, Renming Liu, Feng Shi, Yuying Xie, Jiliang Tang
2023	A	`conf`	Single-Cell Multimodal Prediction via Transformers. CIKM Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
2023	J	`jnl`	Single-Cell Multimodal Prediction via Transformers. CoRR Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
2023	A*	`conf`	Toward Degree Bias in Embedding-Based Knowledge Graph Completion. WWW Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
2023	J	`jnl`	Toward Degree Bias in Embedding-Based Knowledge Graph Completion. CoRR Harry Shomer, Wei Jin, Wentao Wang, Jiliang Tang
2022	A*	`conf`	Automated Self-Supervised Learning for Graphs. ICLR Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
2022	A*	`conf`	Condensing Graphs via One-Step Gradient Matching. KDD Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin
2022	J	`jnl`	Condensing Graphs via One-Step Gradient Matching. CoRR Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bin Ying
2022	J	`jnl`	Deep Learning in Single-Cell Analysis. CoRR Dylan Molho, Jiayuan Ding, Zhaoheng Li, Hongzhi Wen, Wenzhuo Tang, Yixin Wang, Julian Venegas, Wei Jin, Renming Liu, Runze Su, Patrick Danaher, Robert Yang, Yu Leo Lei, Yuying Xie, Jiliang Tang
2022	J	`jnl`	Empowering Graph Representation Learning with Test-Time Graph Transformation. CoRR Wei Jin, Tong Zhao, Jiayuan Ding, Yozen Liu, Jiliang Tang, Neil Shah
2022	A*	`conf`	Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. KDD Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang
2022	J	`jnl`	Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang
2022	A*	`conf`	From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. ICLR Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
2022	A*	`conf`	Graph Condensation for Graph Neural Networks. ICLR Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
2022	A*	`conf`	Graph Neural Networks for Multimodal Single-Cell Data Integration. KDD Hongzhi Wen, Jiayuan Ding, Wei Jin, Yiqi Wang, Yuying Xie, Jiliang Tang
2022	J	`jnl`	Graph Neural Networks for Multimodal Single-Cell Data Integration. CoRR Hongzhi Wen, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
2022	A*	`conf`	Graph Trend Filtering Networks for Recommendation. SIGIR Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
2022	J	`jnl`	Learning Representations for Hyper-Relational Knowledge Graphs. CoRR Harry Shomer, Wei Jin, Juan-Hui Li, Yao Ma, Jiliang Tang
2022	A	`conf`	Localized Graph Collaborative Filtering. SDM Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie, Jiliang Tang
2022	J	`jnl`	Test-Time Training for Graph Neural Networks. CoRR Yiqi Wang, Chaozhuo Li, Wei Jin, Rui Li, Jianan Zhao, Jiliang Tang, Xing Xie
2022	A	`conf`	Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. WSDM Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
2022	J	`jnl`	Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. CoRR Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
2021	J	`jnl`	Automated Self-Supervised Learning for Graphs. CoRR Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
2021	A*	`conf`	DeepRobust: a Platform for Adversarial Attacks and Defenses. AAAI Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
2021	A*	`conf`	Elastic Graph Neural Networks. ICML Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
2021	J	`jnl`	Elastic Graph Neural Networks. CoRR Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
2021	J	`jnl`	From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. CoRR Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
2021	J	`jnl`	Graph Condensation for Graph Neural Networks. CoRR Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah
2021	A	`conf`	Graph Feature Gating Networks. CIKM Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang
2021	J	`jnl`	Graph Feature Gating Networks. CoRR Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang
2021	A	`conf`	Graph Mining with Graph Neural Networks. WSDM Wei Jin
2021	A*	`conf`	Graph Neural Networks with Adaptive Residual. NeurIPS Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang
2021	A*	`conf`	Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu
2021	J	`jnl`	Graph Trend Networks for Recommendations. CoRR Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
2021	J	`jnl`	Jointly Attacking Graph Neural Network and its Explanations. CoRR Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
2021	J	`jnl`	Localized Graph Collaborative Filtering. CoRR Yiqi Wang, Chaozhuo Li, Mingzheng Li, Wei Jin, Yuming Liu, Hao Sun, Xing Xie
2021	A	`conf`	Node Similarity Preserving Graph Convolutional Networks. WSDM Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang
2021	—	`conf`	The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. ACL/IJCNLP (Findings) Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang
2021	J	`jnl`	The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. CoRR Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang
2020	J	`jnl`	Adversarial Attacks and Defenses on Graphs. SIGKDD Explor. Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang
2020	J	`jnl`	Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study. CoRR Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Jiliang Tang
2020	A*	`conf`	Adversarial Attacks and Defenses: Frontiers, Advances and Practice. KDD Han Xu, Yaxin Li, Wei Jin, Jiliang Tang
2020	J	`jnl`	DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses. CoRR Yaxin Li, Wei Jin, Han Xu, Jiliang Tang
2020	A*	`conf`	Graph Structure Learning for Robust Graph Neural Networks. KDD Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang
2020	J	`jnl`	Graph Structure Learning for Robust Graph Neural Networks. CoRR Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang
2020	J	`jnl`	Node Similarity Preserving Graph Convolutional Networks. CoRR Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang
2020	J	`jnl`	Self-supervised Learning on Graphs: Deep Insights and New Direction. CoRR Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, Jiliang Tang
2020	A*	`conf`	Traffic Flow Prediction via Spatial Temporal Graph Neural Network. WWW Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang, Jiliang Tang, Caiyan Jia, Jian Yu