Publication

# denotes visiting or intern students supervised by me, * denotes corresponding authors.

  1. Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing
    Yaodong Yang, Guangyong Chen*, Weixun Wang, Xiaotian Hao, Jianye HAO, , Pheng-Ann Heng
    The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS),CCF A 2022.

  2. Heterogeneous Graph Neural Network-based Imitation Learning for Gate Sizing Acceleration
    2. Xinyi Zhou, Junjie Ye, Chak-Wa Pui, Kun Shao, Guangliang Zhang, Bin Wang, Jianye Hao, Guangyong Chen*, Pheng Ann Heng.
    2022 International Conference on Computer-Aided Design (ICCAD),CCF B 2022.

  3. Acknowledging the Unknown for Multi-label Learning with Single Positive Labels
    Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen*, Pheng-Ann Heng
    European Conference on Computer Vision 2022 (ECCV), 2022.

  4. Flat-aware Cross-stage Distilled Framework for Imbalanced Medical Image Classification.
    Jinpeng Li, Guangyong Chen*, Hangyu Mao, Danruo Deng, Dong Li, Jianye Hao, Qi Dou, Pheng-Ann Heng.
    Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022. (Early accept), 2022.

  5. Explore More Guidance: A Task-aware Instruction Network for Sign Language Translation Enhanced with Data Augmentation
    Yong Cao, Wei Li, Xianzhi Li, Min Chen, Guangyong Chen, Long Hu, Zhengdao Li, Kai Hwang
    2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022.

  6. Data transmission with up to 100 orbital angular momentum modes via commercial multi-mode fiber and parallel neural networks
    Fu Feng, Jia-An Gan, Jingpeng Nong, Peng-Fei Chen, Guangyong Chen, Changjun Min, Xiaocong Yuan, and Michael Somekh
    Optics Express, JCR Q2, Editor's Pick, 2022.

  7. Approximate Range Thresholding
    Zhuo Zhang , Junhao Gan , Zhifeng Bao , Seyed Mohammad Hussein Kazemi , Guangyong Chen , Fengyuan Zhu
    Proceedings of the 2022 International Conference on Management of Data(SIGMOD), CCF A, 2022.

  8. Deep Learning-Enabled Orbital Angular Momentum-Based Information Encryption Transmission.
    Fu Feng, Junbao Hu, Zefeng Guo, Jia-An Gan, Peng-Fei Chen, Guangyong Chen, Changjun Min, Xiaocong Yuan, and Michael Somekh*
    ACS Photonics, JCR Q2, IF: 7.52, 2022.

  9. LHNN: Lattice Hypergraph Neural Network for VLSI Congestion Prediction.
    Bowen Wang, Guibao Shen, Dong Li, Jianye Hao, Wulong Liu, Yu Huang, Hongzhong Wu, Yibo Lin, Guangyong Chen* and Pheng Ann Heng
    Design Automation Conference (DAC), CCF A, 2022.

  10. Accelerated Prediction of Cu-based Single-Atom Alloy Catalysts for CO2 Reduction by Machine Learning.
    Dashuai Wang, Runfeng Cao, Shaogang Hao, Chen Liang, Guangyong Chen, Pengfei Chen, Yang Lie, Xiaolong Zou
    Green Energy & Environment, JCR Q1, IF: 8.21, 2021.

  11. Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning.
    Danruo Deng, Guangyong Chen*, Jianye Hao, Qiong Wang, Pheng-Ann Heng.
    2021 Conference on Neural Information Processing Systems (NeurIPS), CCF A, 2021.

  12. Learning Regularizer for Monocular Depth Estimation with Adversarial Guidance.
    Guibao Shen#, Yingkui Zhang, jialu Li, Mingqiang Wei, Qiong Wang*, Guangyong Chen*, Pheng-Ann Heng.
    The 29th ACM International Conference on Multimedia (ACMMM), CCF A, 2021.

  13. A Rotation-invariant Framework for Deep Point Cloud Analysis.
    Xianzhi Li, Ruihui Li, Guangyong Chen, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng.
    IEEE Transactions on Visualization and Computer Graphics (TVCG), JCR Q1, IF: 4.579, 2021.

  14. RetroPrime: A Chemistry-Inspired and Transformer-based Method for Retro-synthesis Predictions.
    Xiaorui Wang, Yuquan Li, Jiezhong Qiu, Guangyong Chen, Huanxiang Liu, Benben Liao, Chang-Yu Hsieh, Xiaojun Yao
    Chemical Engineering Journal, JCR Q1, IF: 13.27, 2021.

  15. Hyperbolic Relational Graph Convolution Networks Plus: a Simple but Highly Efficient QSAR-modeling Method.
    Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dongsheng Cao, Tingjun Hou
    Briefings in Bioinformatics, JCR Q1, IF: 11.62, 2021.

  16. Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.
    Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng Cao, Jian Wu & Tingjun Hou*
    Journal of Cheminformatics, JCR Q1, IF: 5.51, 2021.

  17. Noise against noise: stochastic label noise helps combat inherent label noise.
    Pengfei Chen#, Guangyong Chen*, Junjie Ye*, Jingwei Zhao, Pheng Ann Heng.
    Ninth International Conference on Learning Representations (ICLR, Top Conference @ AI), Spotlight, 2021.

  18. Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise.
    Pengfei Chen#, Junjie Ye*, Guangyong Chen*, Jingwei Zhao, Pheng Ann Heng.
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, CCF A), 2021.

  19. Robustness of Accuracy Metric and its Inspiration in Learning with Noisy Labels.
    Pengfei Chen#, Junjie Ye*, Guangyong Chen*, Jingwei Zhao, Pheng Ann Heng.
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, CCF A), 2021.

  20. Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction.
    Hongyao Tang#, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen, Yaodong Yang, Luo Zhang, Wulong Liu, Jianye Hao
    Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI, CCF A), 2021.

  21. Q-value Path Decomposition for Deep Multiagent Reinforcement Learning.
    Yaodong Yang#, Jianye Hao, Guangyong Chen*, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei.
    Thirty-seventh International Conference on Machine Learning (ICML, CCF A), 2020.

  22. Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning.
    Weiwen Liu#, Feng Liu, Ruiming Tang*, Ben Liao, Guangyong Chen*, Pheng Ann Heng.
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020.

  23. PMD: An Optimal Transportation-Based User Distance for Recommender Systems.
    Yitong Meng#, Xinyan Dai, Xiao Yan, James Cheng, Weiwen Liu, Jun Guo, Benben Liao, Guangyong Chen.
    European Conference on Information Retrieval (ECIR), 2020.

  24. Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels.
    Pengfei Chen#, Benben Liao, Guangyong Chen*, Shengyu Zhang.
    Thirty-sixth International Conference on Machine Learning (ICML, CCF A), 2019.

  25. Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models.
    Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard Zemel, Shengyu Zhang.
    Representation Learning on Graphs and Manifolds, ICLR 2019 workshop.(Alchemy Contest)

  26. Psrec: Social Recommendation with Pseudo Ratings.
    Yitong Meng, Guangyong Chen, Jiajin Li, Shengyu Zhang.
    Proceedings of the 12th ACM Conference on Recommender Systems (RecSys), 2018.

  27. Large-Scale Bayesian Probabilistic Matrix Factorization with Memo-Free Distributed Variational Inference.
    Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng.
    ACM Transactions on Knowledge Discovery from Data (TKDD, JCR Q1, IF: 4.71 ) 12.3 (2018): 1-24.

  28. Efficient and Robust Emergence of Norms through Heuristic Collective Learning.
    Jianye Hao, Jun Sun Sun, Guangyong Chen, Zan Wang, Chao Yu, Zhong Ming.
    ACM Transactions on Autonomous and Adaptive Systems (TAAS, CCF B) 12.4 (2017): 1-20.

  29. Learning to Aggregate Ordinal Labels by Maximizing Separating Width.
    Guangyong Chen, Shengyu Zhang, Di Lin, Hui Huang, Pheng Ann Heng.
    Thirty-fourth International Conference on Machine Learning (ICML, CCF A) , 2017.

  30. Cascaded Feature Network for Semantic Segmentation of RGB-D Images.
    Di Lin, Guangyong Chen, Daniel Cohen-Or, Pheng-Ann Heng, Hui Huang.
    In Proceedings of the IEEE International Conference on Computer Vision (ICCV, CCF A), 2017.

  31. A Bayesian Nonparametric Approach to Dynamic Dyadic Data Prediction.
    Fengyuan Zhu, Guangyong Chen, Pheng-Ann Heng.
    IEEE 16th International Conference on Data Mining (ICDM, CCF B), 2016

  32. Blind Image Denoising via Dependent Dirichlet Process Tree.
    Fengyuan Zhu, Guangyong Chen *, Jianye Hao, Pheng-Ann Heng.
    IEEE transactions on pattern analysis and machine intelligence (TPAMI, CCF A, JCR Q1, IF: 16.39), 39.8, (2016): 1518-1531.

  33. From Noise Modeling to Blind Image Denoising.
    Fengyuan Zhu, Guangyong Chen, Pheng-Ann Heng.
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR, CCF A), 2016.

  34. An Efficient Statistical Method for Image Noise Level Estimation.
    Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng.
    In Proceedings of the IEEE International Conference on Computer Vision (ICCV, CCF A), 2015.