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2020 – today
- 2024
[j10]Hongxia Deng
, Dongsheng Luo, Zijing Zhou, Jinxiu Hou, Guanyu Qian, Haifang Li:
Leaf disease recognition based on channel information attention network. Multim. Tools Appl. 83(3): 6601-6619 (2024)- [j9]Dongsheng Luo, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Wenchao Yu, Xiao Liu, Haifeng Chen, Xiang Zhang:
Towards Inductive and Efficient Explanations for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5245-5259 (2024) - [c31]Rundong Huang, Farhad Shirani, Dongsheng Luo:
Factorized Explainer for Graph Neural Networks. AAAI 2024: 12626-12634 - [c30]Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Shape-aware Graph Spectral Learning. CIKM 2024: 2692-2701 - [c29]Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen:
Explaining Time Series via Contrastive and Locally Sparse Perturbations. ICLR 2024 - [c28]Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo:
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks. ICLR 2024 - [c27]Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo:
Parametric Augmentation for Time Series Contrastive Learning. ICLR 2024 - [c26]Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mondal, Hua Wei, Dongsheng Luo:
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks. ICML 2024 - [c25]Zichuan Liu, Tianchun Wang, Jimeng Shi, Xu Zheng, Zhuomin Chen, Lei Song, Wenqian Dong, Jayantha Obeysekera, Farhad Shirani, Dongsheng Luo:
TimeX++: Learning Time-Series Explanations with Information Bottleneck. ICML 2024 - [c24]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD 2024: 4479-4489 - [c23]Behzad Ousat, Dongsheng Luo, Amin Kharraz:
Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models. WWW (Companion Volume) 2024: 646-649 - [i35]Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen:
Explaining Time Series via Contrastive and Locally Sparse Perturbations. CoRR abs/2401.08552 (2024) - [i34]Qianying Ren, Dongsheng Luo, Dongjin Song:
Rank Supervised Contrastive Learning for Time Series Classification. CoRR abs/2401.18057 (2024) - [i33]Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, Dongsheng Luo:
Interpreting Graph Neural Networks with In-Distributed Proxies. CoRR abs/2402.02036 (2024) - [i32]Xu Zheng, Farhad Shirani, Tianchun Wang, Shouwei Gao, Wenqian Dong, Wei Cheng, Dongsheng Luo:
PAC Learnability under Explanation-Preserving Graph Perturbations. CoRR abs/2402.05039 (2024) - [i31]Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo:
Parametric Augmentation for Time Series Contrastive Learning. CoRR abs/2402.10434 (2024) - [i30]Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng, Jian-Zhe Wang, Chun-Cheng Chug, Min-Chen Hsieh, Yun-Chien Tseng, Ling Chen, Dongsheng Luo, Chi-Te Wang, Pei-fu Chen, Feng Liu, Fang-Ming Hung:
Large Language Multimodal Models for 5-Year Chronic Disease Cohort Prediction Using EHR Data. CoRR abs/2403.04785 (2024) - [i29]Tiejin Chen, Wenwang Huang, Linsey Pang, Dongsheng Luo, Hua Wei:
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape. CoRR abs/2403.06013 (2024) - [i28]Guoming Li, Jian Yang, Shangsong Liang, Dongsheng Luo:
Spectral GNN via Two-dimensional (2-D) Graph Convolution. CoRR abs/2404.04559 (2024) - [i27]Guoming Li, Jian Yang, Shangsong Liang, Dongsheng Luo:
Elevating Spectral GNNs through Enhanced Band-pass Filter Approximation. CoRR abs/2404.15354 (2024) - [i26]Zichuan Liu, Tianchun Wang, Jimeng Shi, Xu Zheng, Zhuomin Chen, Lei Song, Wenqian Dong, Jayantha Obeysekera, Farhad Shirani, Dongsheng Luo:
TimeX++: Learning Time-Series Explanations with Information Bottleneck. CoRR abs/2405.09308 (2024) - [i25]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR abs/2406.10425 (2024) - [i24]Jiaxing Zhang, Jiayi Liu, Dongsheng Luo, Jennifer Neville, Hua Wei:
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation. CoRR abs/2407.15351 (2024) - [i23]Aitian Ma, Dongsheng Luo, Mo Sha:
MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series Forecasting. CoRR abs/2410.02070 (2024) - [i22]Aitian Ma, Dongsheng Luo, Mo Sha:
MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters. CoRR abs/2410.02081 (2024) - [i21]Xu Zheng, Farhad Shirani, Zhuomin Chen, Chaohao Lin, Wei Cheng, Wenbo Guo, Dongsheng Luo:
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI. CoRR abs/2410.02970 (2024) - 2023
- [j8]Hongxia Deng, Guanyu Qian, Dongsheng Luo, Xindong Lv, Haoqi Liu, Haifang Li:
MRS-Net: an image inpainting algorithm with multi-scale residual attention fusion. Appl. Intell. 53(7): 7497-7511 (2023) - [j7]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. 14(5): 92:1-92:23 (2023) - [j6]Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Bill Yu, Jun Huan, Xiao Liu, Xiang Zhang:
Random Walk on Multiple Networks. IEEE Trans. Knowl. Data Eng. 35(8): 8417-8430 (2023) - [c22]Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Time Series Contrastive Learning with Information-Aware Augmentations. AAAI 2023: 4534-4542 - [c21]Xu Zheng, Tianchun Wang, Samin Yasar Chowdhury, Ruimin Sun, Dongsheng Luo:
Unsafe Behavior Detection with Adaptive Contrastive Learning in Industrial Control Systems. EuroS&P Workshops 2023: 363-369 - [c20]Jiaxing Zhang, Dongsheng Luo, Hua Wei:
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation. KDD 2023: 3286-3296 - [c19]Minghao Lin, Minghao Cheng, Dongsheng Luo, Yueqi Chen:
CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning. SpaceSec 2023 - [c18]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM 2023: 634-642 - [i20]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR abs/2301.02791 (2023) - [i19]Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Time Series Contrastive Learning with Information-Aware Augmentations. CoRR abs/2303.11911 (2023) - [i18]Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang:
Self-Explainable Graph Neural Networks for Link Prediction. CoRR abs/2305.12578 (2023) - [i17]Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Bill Yu, Jun Huan, Xiao Liu, Xiang Zhang:
Random Walk on Multiple Networks. CoRR abs/2307.01637 (2023) - [i16]Jiaxing Zhang, Dongsheng Luo, Hua Wei:
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation. CoRR abs/2307.07832 (2023) - [i15]Jiaxing Zhang, Zhuomin Chen, Hao Mei, Dongsheng Luo, Hua Wei:
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Task. CoRR abs/2307.07840 (2023) - [i14]Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo:
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks. CoRR abs/2310.01820 (2023) - [i13]Minghao Lin, Minghao Cheng, Dongsheng Luo, Yueqi Chen:
CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning. CoRR abs/2310.08210 (2023) - [i12]Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Learning Graph Filters for Spectral GNNs via Newton Interpolation. CoRR abs/2310.10064 (2023) - [i11]Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang:
DyExplainer: Explainable Dynamic Graph Neural Networks. CoRR abs/2310.16375 (2023) - [i10]Rundong Huang, Farhad Shirani, Dongsheng Luo:
Factorized Explainer for Graph Neural Networks. CoRR abs/2312.05596 (2023) - 2022
- [j5]Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, Jinpeng Huai:
A Collective Approach to Scholar Name Disambiguation. IEEE Trans. Knowl. Data Eng. 34(5): 2020-2032 (2022) - [c17]Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang:
Personalized Federated Learning via Heterogeneous Modular Networks. ICDM 2022: 1197-1202 - [c16]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG 2022: 37 - [i9]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
On Consistency in Graph Neural Network Interpretation. CoRR abs/2205.13733 (2022) - [i8]Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang:
Personalized Federated Learning via Heterogeneous Modular Networks. CoRR abs/2210.14830 (2022) - [i7]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR abs/2212.08689 (2022) - 2021
- [j4]Hongxia Deng, Dongsheng Luo, Zhangwei Chang, Haifang Li, Xiaofeng Yang:
RAHC_GAN: A Data Augmentation Method for Tomato Leaf Disease Recognition. Symmetry 13(9): 1597 (2021) - [c15]Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, Jinpeng Huai:
A Collective Approach to Scholar Name Disambiguation (Extended Abstract). ICDE 2021: 2317-2318 - [c14]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang:
InfoGCL: Information-Aware Graph Contrastive Learning. NeurIPS 2021: 30414-30425 - [c13]Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang:
Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection. SDM 2021: 91-99 - [c12]Dongsheng Luo, Wei Cheng, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang:
Learning to Drop: Robust Graph Neural Network via Topological Denoising. WSDM 2021: 779-787 - [i6]Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang:
Unsupervised Document Embedding via Contrastive Augmentation. CoRR abs/2103.14542 (2021) - [i5]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang:
InfoGCL: Information-Aware Graph Contrastive Learning. CoRR abs/2110.15438 (2021) - 2020
- [j3]Yuchen Bian, Dongsheng Luo, Yaowei Yan, Wei Cheng, Wei Wang, Xiang Zhang:
Memory-based random walk for multi-query local community detection. Knowl. Inf. Syst. 62(5): 2067-2101 (2020) - [j2]Yuchen Bian, Dongsheng Luo, Yaowei Yan, Wei Cheng, Wei Wang, Xiang Zhang:
Correction to: Memory-based random walk for multi-query local community detection. Knowl. Inf. Syst. 62(5): 2103-2104 (2020) - [c11]Hongxia Deng, Zijian Feng, Ying Liu, Dongsheng Luo, Xiaofeng Yang, Haifang Li:
Face Recognition Algorithm Based on Weighted Intensity PCNN. CBD 2020: 207-212 - [c10]Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang:
Local Community Detection in Multiple Networks. KDD 2020: 266-274 - [c9]Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang:
Parameterized Explainer for Graph Neural Network. NeurIPS 2020 - [c8]Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Bill Yu, Xiang Zhang:
Deep Multi-Graph Clustering via Attentive Cross-Graph Association. WSDM 2020: 393-401 - [i4]Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang:
Parameterized Explainer for Graph Neural Network. CoRR abs/2011.04573 (2020) - [i3]Dongsheng Luo, Yuchen Bian, Xiang Zhang, Jun Huan:
Attentive Social Recommendation: Towards User And Item Diversities. CoRR abs/2011.04797 (2020) - [i2]Dongsheng Luo, Wei Cheng, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang:
Learning to Drop: Robust Graph Neural Network via Topological Denoising. CoRR abs/2011.07057 (2020)
2010 – 2019
- 2019
- [j1]Dongsheng Luo, Wei Wei, Yumei Liao, Hongyong Deng:
Bang-Bang Property of Time Optimal Control for a Kind of Microwave Heating Problem. J. Optim. Theory Appl. 183(1): 317-331 (2019) - [c7]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang:
Adaptive Neural Network for Node Classification in Dynamic Networks. ICDM 2019: 1402-1407 - [c6]Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiao Liu, Xiang Zhang:
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs. IJCAI 2019: 3947-3953 - [c5]Yaowei Yan, Yuchen Bian, Dongsheng Luo, Dongwon Lee, Xiang Zhang:
Constrained Local Graph Clustering by Colored Random Walk. WWW 2019: 2137-2146 - 2018
- [c4]Shuai Ma, Chen Gong, Renjun Hu, Dongsheng Luo, Chunming Hu, Jinpeng Huai:
Query Independent Scholarly Article Ranking. ICDE 2018: 953-964 - [c3]Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, Xiang Zhang:
On Multi-query Local Community Detection. ICDM 2018: 9-18 - [c2]Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Bill Yu, John Yen, Xiang Zhang:
Local Graph Clustering by Multi-network Random Walk with Restart. PAKDD (3) 2018: 490-501 - 2016
- [i1]Dongsheng Luo, Chen Gong, Renjun Hu, Liang Duan, Shuai Ma:
Ensemble Enabled Weighted PageRank. CoRR abs/1604.05462 (2016)
2000 – 2009
- 2004
- [c1]Dongsheng Luo, Xiang Xie, Jingming Kuang:
Integrating tonal information into Mandarin name recognition with different strategies. ISCSLP 2004: 265-268
Coauthor Index
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