| Comparison of directed and weighted co-occurrence networks of six languages Y Gao, W Liang, Y Shi, Q Huang Physica A: Statistical Mechanics and its Applications 393, 579-589, 2014 | 60 | 2014 |
| Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting Y Gao, L Zhao, L Wu, Y Ye, H Xiong, C Yang The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 2019 | 37 | 2019 |
| Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting Y Gao, L Zhao Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), 2018 | 35 | 2018 |
| Gnes: Learning to explain graph neural networks Y Gao, T Sun, R Bhatt, D Yu, S Hong, L Zhao 2021 IEEE International Conference on Data Mining (ICDM), 131-140, 2021 | 33 | 2021 |
| Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Y Gao, S Gu, J Jiang, SR Hong, D Yu, L Zhao ACM Computing Surveys, 2022 | 29 | 2022 |
| Aligning eyes between humans and deep neural network through interactive attention alignment Y Gao, TS Sun, L Zhao, SR Hong Proceedings of the ACM on Human-Computer Interaction 6 (CSCW2), 1-28, 2022 | 28 | 2022 |
| Res: A robust framework for guiding visual explanation Y Gao, TS Sun, G Bai, S Gu, SR Hong, Z Liang proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 26 | 2022 |
| Dyngraph2seq: Dynamic-graph-to-sequence interpretable learning for health stage prediction in online health forums Y Gao, L Wu, H Homayoun, L Zhao 2019 IEEE International Conference on Data Mining (ICDM), 1042-1047, 2019 | 23 | 2019 |
| BEAN: Interpretable and efficient learning with biologically-enhanced artificial neuronal assembly regularization Y Gao, GA Ascoli, L Zhao Frontiers in Neurorobotics 15, 567482, 2021 | 17 | 2021 |
| Spatio-temporal event forecasting using incremental multi-source feature learning L Zhao, Y Gao, J Ye, F Chen, Y Ye, CT Lu, N Ramakrishnan ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (2), 1-28, 2021 | 15 | 2021 |
| Incomplete label uncertainty estimation for petition victory prediction with dynamic features J Wang, Y Gao, A Züfle, J Yang, L Zhao 2018 IEEE International Conference on Data Mining (ICDM), 537-546, 2018 | 15 | 2018 |
| Local event forecasting and synthesis using unpaired deep graph translations Y Gao, X Guo, L Zhao Proceedings of the 2nd ACM SIGSPATIAL Workshop on Analytics for Local Events …, 2018 | 8 | 2018 |
| Essa: Explanation iterative supervision via saliency-guided data augmentation S Gu, Y Zhang, Y Gao, X Yang, L Zhao Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 5 | 2023 |
| Modeling health stage development of patients with dynamic attributed graphs in online health communities Y Gao, T Chowdhury, L Wu, L Zhao IEEE Transactions on Knowledge and Data Engineering 35 (2), 1831-1843, 2022 | 5 | 2022 |
| Schematic memory persistence and transience for efficient and robust continual learning Y Gao, GA Ascoli, L Zhao Neural Networks 144, 49-60, 2021 | 5 | 2021 |
| Designing a direct feedback loop between humans and Convolutional Neural Networks through local explanations TS Sun, Y Gao, S Khaladkar, S Liu, L Zhao, YH Kim, SR Hong Proceedings of the ACM on Human-Computer Interaction 7 (CSCW2), 1-32, 2023 | 4 | 2023 |
| Magi: Multi-annotated explanation-guided learning Y Zhang, S Gu, Y Gao, B Pan, X Yang, L Zhao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
| Saliency-augmented memory completion for continual learning G Bai, C Ling, Y Gao, L Zhao Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 3 | 2023 |
| Functional connectivity prediction with deep learning for graph transformation N Etemadyrad, Y Gao, Q Li, X Guo, F Krueger, Q Lin, D Qiu, L Zhao IEEE Transactions on Neural Networks and Learning Systems, 2022 | 2 | 2022 |
| Online dynamic multi-source feature learning and its application to spatio-temporal event forecasting L Zhao, Y Gao ACM transactions on knowledge discovery from data, 2021 | 2 | 2021 |
Liang ZhaoEmory University在 emory.edu 的电子邮件经过验证
