Yanqiao Zhu

According to our database, Yanqiao Zhu authored at least 53 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Molecular Contrastive Pretraining with Collaborative Featurizations.

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

J. Chem. Inf. Model., February, 2024

An Evaluation of Large Language Models in Bioinformatics Research.

Hengchuang Yin, Zhonghui Gu, Fanhao Wang, Yiparemu Abuduhaibaier, Yanqiao Zhu, Xinming Tu, Xian-Sheng Hua, Xiao Luo, Yizhou Sun

CoRR, 2024

2023

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu

ACM Trans. Intell. Syst. Technol., October, 2023

Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation.

Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang

IEEE Trans. Knowl. Data Eng., September, 2023

BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks.

Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang

IEEE Trans. Medical Imaging, February, 2023

GSLB: The Graph Structure Learning Benchmark.

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

CoRR, 2023

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.

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

CoRR, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2023

SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models.

Xiaoxuan Wang, Ziniu Hu, Pan Lu, Yanqiao Zhu, Jieyu Zhang, Satyen Subramaniam, Arjun R. Loomba, Shichang Zhang, Yizhou Sun, Wei Wang

CoRR, 2023

Code Recommendation for Open Source Software Developers.

Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun, Wei Wang

Proceedings of the ACM Web Conference 2023, 2023

GSLB: The Graph Structure Learning Benchmark.

Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

M²Hub: Unlocking the Potential of Machine Learning for Materials Discovery.

Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John M. Gregoire, Carla Pedro Gomes

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis.

Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

A Systematic Survey of Chemical Pre-trained Models.

Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange.

Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Neighborhood-Regularized Self-Training for Learning with Few Labels.

Ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce C. Ho, Chao Zhang, Carl Yang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Survey on Pretrained Language Models for Neural Code Intelligence.

Yichen Xu, Yanqiao Zhu

CoRR, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks.

Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

CoRR, 2022

A Systematic Survey of Molecular Pre-trained Models.

Jun Xia, Yanqiao Zhu, Yuanqi Du, Yue Liu, Stan Z. Li

CoRR, 2022

Improving Molecular Pretraining with Complementary Featurizations.

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

CoRR, 2022

A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications.

Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li

CoRR, 2022

Structure-Enhanced Heterogeneous Graph Contrastive Learning.

Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis.

Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

The First Learning on Graphs Conference: Preface.

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

Proceedings of the Learning on Graphs Conference, 2022

A Survey on Deep Graph Generation: Methods and Applications.

Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu

Proceedings of the Learning on Graphs Conference, 2022

Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning.

Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis.

Yanqiao Zhu, Hejie Cui, Lifang He, Lichao Sun, Carl Yang

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Deep Contrastive Multiview Network Embedding.

Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract).

Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

Proceedings of the IEEE International Conference on Big Data, 2022

BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks (Extended Abstract).

Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang

Proceedings of the IEEE International Conference on Big Data, 2022

2021

GraphAIR: Graph representation learning with neighborhood aggregation and interaction.

Fenyu Hu, Yanqiao Zhu, Shu Wu, Weiran Huang, Liang Wang, Tieniu Tan

Pattern Recognit., 2021

Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation.

Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, Liang Wang

CoRR, 2021

Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning.

Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu

CoRR, 2021

Deep Contrastive Learning for Multi-View Network Embedding.

Mengqi Zhang, Yanqiao Zhu, Shu Wu, Liang Wang

CoRR, 2021

BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis.

Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang

CoRR, 2021

Graph Symbiosis Learning.

Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li

CoRR, 2021

Deep Graph Structure Learning for Robust Representations: A Survey.

Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2021

Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2021

Graph Contrastive Learning with Adaptive Augmentation.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the WWW '21: The Web Conference 2021, 2021

An Empirical Study of Graph Contrastive Learning.

Yanqiao Zhu, Yichen Xu, Qiang Liu, Shu Wu

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Mining Latent Structures for Multimedia Recommendation.

Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, Liang Wang

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction.

Yichen Xu, Yanqiao Zhu, Feng Yu, Qiang Liu, Shu Wu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Deep Active Learning for Text Classification with Diverse Interpretations.

Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Deep Active Graph Representation Learning.

Yanqiao Zhu, Weizhi Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2020

CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning.

Yanqiao Zhu, Yichen Xu, Feng Yu, Shu Wu, Liang Wang

CoRR, 2020

Deep Graph Contrastive Representation Learning.

Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2020

TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation.

Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

2019

Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks.

Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang, Tieniu Tan

CoRR, 2019

Tripartite Active Learning for Interactive Anomaly Discovery.

Yanqiao Zhu, Kai Yang

IEEE Access, 2019

Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification.

Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang, Tieniu Tan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Session-Based Recommendation with Graph Neural Networks.

Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Active Learning for Wireless IoT Intrusion Detection.

Kai Yang, Jie Ren, Yanqiao Zhu, Weiyi Zhang

IEEE Wirel. Commun., 2018