| Twitter discussions and emotions about the COVID-19 pandemic: Machine learning approach J Xue, J Chen, R Hu, C Chen, C Zheng, Y Su, T Zhu Journal of medical Internet research 22 (11), e20550, 2020 | 421 | 2020 |
| Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter J Xue, J Chen, C Chen, C Zheng, S Li, T Zhu PloS one 15 (9), e0239441, 2020 | 360 | 2020 |
| The hidden pandemic of family violence during COVID-19: unsupervised learning of tweets J Xue, J Chen, C Chen, R Hu, T Zhu Journal of medical Internet research 22 (11), e24361, 2020 | 212 | 2020 |
| Examining the impact of COVID-19 lockdown in Wuhan and Lombardy: a psycholinguistic analysis on Weibo and Twitter Y Su, J Xue, X Liu, P Wu, J Chen, C Chen, T Liu, W Gong, T Zhu International journal of environmental research and public health 17 (12), 4552, 2020 | 156 | 2020 |
| Explanation by progressive exaggeration S Singla, B Pollack, J Chen, K Batmanghelich The Eighth International Conference on Learning Representations (ICLR 2020), 2019 | 121 | 2019 |
| Hierarchical amortized GAN for 3D high resolution medical image synthesis L Sun, J Chen, Y Xu, M Gong, K Yu, K Batmanghelich IEEE journal of biomedical and health informatics 26 (8), 3966-3975, 2022 | 87 | 2022 |
| Weakly supervised disentanglement by pairwise similarities J Chen, K Batmanghelich Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3495-3502, 2020 | 68 | 2020 |
| Interpretable clustering via discriminative rectangle mixture model J Chen, Y Chang, B Hobbs, P Castaldi, M Cho, E Silverman, J Dy 2016 IEEE 16th international conference on data mining (ICDM), 823-828, 2016 | 54 | 2016 |
| Using Data Mining Techniques to Examine Domestic Violence Topics on Twitter J Xue, J Chen, R Gelles Violence and Gender 6 (2), 105-114, 2019 | 42 | 2019 |
| Generative-discriminative complementary learning Y Xu, M Gong, J Chen, T Liu, K Zhang, K Batmanghelich Proceedings of the AAAI conference on artificial intelligence 34 (04), 6526-6533, 2020 | 38 | 2020 |
| Transforming complex problems into K-means solutions H Liu, J Chen, J Dy, Y Fu IEEE transactions on pattern analysis and machine intelligence 45 (7), 9149-9168, 2023 | 30 | 2023 |
| A Bayesian nonparametric model for disease subtyping: application to emphysema phenotypes JC Ross, PJ Castaldi, MH Cho, J Chen, Y Chang, JG Dy, EK Silverman, ... IEEE transactions on medical imaging 36 (1), 343-354, 2016 | 28 | 2016 |
| Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model J Chen, W Dai, Y Sun, J Dy Proc. of the 2015 SIAM Int. Conf. on Data Mining (SDM'15), 2015 | 23 | 2015 |
| Multiple clustering views from multiple uncertain experts Y Chang, J Chen, MH Cho, PJ Castaldi, EK Silverman, JG Dy International Conference on Machine Learning, 674-683, 2017 | 16 | 2017 |
| DrasCLR: A self-supervised framework of learning disease-related and anatomy-specific representation for 3D lung CT images K Yu, L Sun, J Chen, M Reynolds, T Chaudhary, K Batmanghelich Medical Image Analysis 92, 103062, 2024 | 13 | 2024 |
| Hierarchical amortized training for memory-efficient high resolution 3D GAN L Sun, J Chen, Y Xu, M Gong, K Yu, K Batmanghelich arXiv preprint arXiv:2008.01910, 2020 | 13 | 2020 |
| Clustering with domain-specific usefulness scores Y Chang, J Chen, MH Cho, PJ Castaidi, EK Silverman, JG Dy Proceedings of the 2017 SIAM International Conference on Data Mining, 207-215, 2017 | 13 | 2017 |
| EEGNet-MSD: A sparse convolutional neural network for efficient EEG-based intent decoding R Fu, Z Wang, S Wang, X Xu, J Chen, G Wen IEEE Sensors Journal, 2023 | 12 | 2023 |
| Interpretable clustering methods J Chen Northeastern University, 2018 | 12 | 2018 |
| Recognizing single-trial motor imagery EEG based on interpretable clustering method R Fu, W Li, J Chen, M Han Biomedical Signal Processing and Control 63, 102171, 2021 | 11 | 2021 |
Jia XueAssistant Professor, University of Toronto; University of Pennsylvania, Harvard UniversityVerified email at utoronto.ca
