Yanqiao Zhu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 74

Top Topics

Graph Representation

Top Venues

Publications

Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. ICLR (2024)
Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu
Molecular Contrastive Pretraining with Collaborative Featurizations. J. Chem. Inf. Model. 64 (4) (2024)
Ran Xu, Wenqi Shi, Yue Yu, Yuchen Zhuang, Yanqiao Zhu, May D. Wang, Joyce C. Ho, Chao Zhang, Carl Yang
BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers. CoRR (2024)
Haorui Wang, Marta Skreta, Cher-Tian Ser, Wenhao Gao, Lingkai Kong, Felix Streith-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang
Efficient Evolutionary Search Over Chemical Space with Large Language Models. CoRR (2024)
Hengchuang Yin, Zhonghui Gu, Fanhao Wang, Yiparemu Abuduhaibaier, Yanqiao Zhu, Xinming Tu, Xian-Sheng Hua, Xiao Luo, Yizhou Sun
An Evaluation of Large Language Models in Bioinformatics Research. CoRR (2024)
Chenchen Ye, Ziniu Hu, Yihe Deng, Zijie Huang, Mingyu Derek Ma, Yanqiao Zhu, Wei Wang
MIRAI: Evaluating LLM Agents for Event Forecasting. CoRR (2024)
Ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce C. Ho, Chao Zhang, Carl Yang
Neighborhood-Regularized Self-Training for Learning with Few Labels. CoRR (2023)
Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li
AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange. CIKM (2023)
Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu
GSLB: The Graph Structure Learning Benchmark. CoRR (2023)
Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. CoRR (2023)
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu
GSLB: The Graph Structure Learning Benchmark. NeurIPS (2023)
Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John M. Gregoire, Carla P. Gomes
Hub: Unlocking the Potential of Machine Learning for Materials Discovery. CoRR (2023)
Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li
A Systematic Survey of Chemical Pre-trained Models. IJCAI (2023)
Xiaoxuan Wang, Ziniu Hu, Pan Lu, Yanqiao Zhu, Jieyu Zhang, Satyen Subramaniam, Arjun R. Loomba, Shichang Zhang, Yizhou Sun, Wei Wang
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models. CoRR (2023)
Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan
The Second Learning on Graphs Conference: Preface. LoG (2023)
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu
Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining. ACM Trans. Intell. Syst. Technol. 14 (5) (2023)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang
BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks. IEEE Trans. Medical Imaging 42 (2) (2023)
Ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce C. Ho, Chao Zhang, Carl Yang
Neighborhood-Regularized Self-Training for Learning with Few Labels. AAAI (2023)
Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun, Wei Wang
Code Recommendation for Open Source Software Developers. WWW (2023)
Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang
Uncovering Neural Scaling Laws in Molecular Representation Learning. NeurIPS (2023)
Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang
Uncovering Neural Scaling Laws in Molecular Representation Learning. CoRR (2023)
Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John M. Gregoire, Carla Pedro Gomes
Hub: Unlocking the Potential of Machine Learning for Materials Discovery. NeurIPS (2023)
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis. ISBI (2023)
Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. CoRR (2022)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks (Extended Abstract). Big Data (2022)
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract). Big Data (2022)
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks. CoRR (2022)
Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu
Improving Molecular Pretraining with Complementary Featurizations. CoRR (2022)
Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang
Deep Contrastive Multiview Network Embedding. CIKM (2022)
Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li
A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications. CoRR (2022)
Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. KDD (2022)
Yanqiao Zhu, Hejie Cui, Lifang He, Lichao Sun, Carl Yang
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis. EMBC (2022)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis. CoRR (2022)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis. MICCAI (8) (2022)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks. CoRR (2022)
Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu
A Survey on Deep Graph Generation: Methods and Applications. CoRR (2022)
Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov
The First Learning on Graphs Conference: Preface. LoG (2022)
Yichen Xu, Yanqiao Zhu
A Survey on Pretrained Language Models for Neural Code Intelligence. CoRR (2022)
Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu
Structure-Enhanced Heterogeneous Graph Contrastive Learning. SDM (2022)
Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu
A Survey on Deep Graph Generation: Methods and Applications. LoG (2022)
Jun Xia, Yanqiao Zhu, Yuanqi Du, Yue Liu, Stan Z. Li
A Systematic Survey of Molecular Pre-trained Models. CoRR (2022)
Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun, Wei Wang
Code Recommendation for Open Source Software Developers. CoRR (2022)
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang
Mining Latent Structures for Multimedia Recommendation. ACM Multimedia (2021)
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang
Mining Latent Structures for Multimedia Recommendation. CoRR (2021)
Yanqiao Zhu, Hejie Cui, Lifang He, Lichao Sun, Carl Yang
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis. CoRR (2021)
Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li
Graph Symbiosis Learning. CoRR (2021)
Fenyu Hu, Yanqiao Zhu, Shu Wu, Weiran Huang, Liang Wang, Tieniu Tan
GraphAIR: Graph representation learning with neighborhood aggregation and interaction. Pattern Recognit. 112 (2021)
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang
Graph Contrastive Learning with Adaptive Augmentation. WWW (2021)
Mengqi Zhang, Yanqiao Zhu, Shu Wu, Liang Wang
Deep Contrastive Learning for Multi-View Network Embedding. CoRR (2021)
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang
Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation. CoRR (2021)
Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu
Deep Active Learning for Text Classification with Diverse Interpretations. CoRR (2021)
Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu
An Empirical Study of Graph Contrastive Learning. CoRR (2021)
Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang
BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis. CoRR (2021)
Yichen Xu, Yanqiao Zhu, Feng Yu, Qiang Liu, Shu Wu
Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction. CIKM (2021)
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang
Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction. CoRR (2021)
Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu
Deep Active Learning for Text Classification with Diverse Interpretations. CIKM (2021)
Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu
An Empirical Study of Graph Contrastive Learning. NeurIPS Datasets and Benchmarks (2021)
Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning. CoRR (2021)
Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang
Deep Graph Structure Learning for Robust Representations: A Survey. CoRR (2021)
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang
Graph Contrastive Learning with Adaptive Augmentation. CoRR (2020)
Yanqiao Zhu, Yichen Xu, Feng Yu, Shu Wu, Liang Wang
CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning. CoRR (2020)
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang
Deep Graph Contrastive Representation Learning. CoRR (2020)
Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation. CoRR (2020)
Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation. SIGIR (2020)
Yanqiao Zhu, Weizhi Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang
Deep Active Graph Representation Learning. CoRR (2020)
Fenyu Hu, Yanqiao Zhu, Shu Wu, Weiran Huang, Liang Wang, Tieniu Tan
GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction. CoRR (2019)
Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang, Tieniu Tan
Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks. CoRR (2019)
Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan
Session-Based Recommendation with Graph Neural Networks. AAAI (2019)
Yanqiao Zhu, Kai Yang
Tripartite Active Learning for Interactive Anomaly Discovery. IEEE Access 7 (2019)
Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang, Tieniu Tan
Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification. IJCAI (2019)
Kai Yang, Jie Ren, Yanqiao Zhu, Weiyi Zhang
Active Learning for Wireless IoT Intrusion Detection. CoRR (2018)
Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan
Session-based Recommendation with Graph Neural Networks. CoRR (2018)
Kai Yang, Jie Ren, Yanqiao Zhu, Weiyi Zhang
Active Learning for Wireless IoT Intrusion Detection. IEEE Wirel. Commun. 25 (6) (2018)