| Generate rather than retrieve: Large language models are strong context generators W Yu, D Iter, S Wang, Y Xu, M Ju, S Sanyal, C Zhu, M Zeng, M Jiang ICLR'23, 2022 | 284 | 2022 |
| -Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States Y Ye, S Hou, Y Fan, Y Zhang, Y Qian, S Sun, Q Peng, M Ju, W Song, ... IEEE Journal of Biomedical and Health Informatics 24 (10), 2755-2764, 2020 | 101* | 2020 |
| Heterogeneous temporal graph neural network Y Fan, M Ju, C Zhang, Y Ye Proceedings of the 2022 SIAM international conference on data mining (SDM …, 2022 | 63 | 2022 |
| Let graph be the go board: gradient-free node injection attack for graph neural networks via reinforcement learning M Ju, Y Fan, C Zhang, Y Ye Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 4383-4390, 2023 | 51* | 2023 |
| Heterogeneous temporal graph transformer: An intelligent system for evolving android malware detection Y Fan, M Ju, S Hou, Y Ye, W Wan, K Wang, Y Mei, Q Xiong Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 51 | 2021 |
| Grape: Knowledge graph enhanced passage reader for open-domain question answering M Ju, W Yu, T Zhao, C Zhang, Y Ye Findings of EMNLP'22, 2022 | 43 | 2022 |
| Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization M Ju, T Zhao, Q Wen, W Yu, N Shah, Y Ye, C Zhang ICLR'23, 2022 | 35 | 2022 |
| Adaptive kernel graph neural network M Ju, S Hou, Y Fan, J Zhao, Y Ye, L Zhao Proceedings of the AAAI conference on artificial intelligence 36 (6), 7051-7058, 2022 | 29 | 2022 |
| Development and validation of a machine learning algorithm for predicting response to anticholinergic medications for overactive bladder syndrome D Sheyn, M Ju, S Zhang, C Anyaeche, A Hijaz, J Mangel, S Mahajan, ... Obstetrics & Gynecology 134 (5), 946-957, 2019 | 29 | 2019 |
| Self-supervised graph structure refinement for graph neural networks J Zhao, Q Wen, M Ju, C Zhang, Y Ye Proceedings of the sixteenth ACM international conference on web search and …, 2023 | 28 | 2023 |
| Chasing all-round graph representation robustness: Model, training, and optimization C Zhang, Y Tian, M Ju, Z Liu, Y Ye, N Chawla, C Zhang The eleventh international conference on learning representations, 2022 | 21 | 2022 |
| Disentangled representation learning in heterogeneous information network for large-scale android malware detection in the COVID-19 era and beyond S Hou, Y Fan, M Ju, Y Ye, W Wan, K Wang, Y Mei, Q Xiong, F Shao Proceedings of the AAAI conference on artificial intelligence 35 (9), 7754-7761, 2021 | 18 | 2021 |
| GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation M Ju, T Zhao, W Yu, N Shah, Y Ye NeurIPS'23, 2023 | 16 | 2023 |
| Community mitigation: A data-driven system for covid-19 risk assessment in a hierarchical manner Y Ye, Y Fan, S Hou, Y Zhang, Y Qian, S Sun, Q Peng, M Ju, W Song, ... Proceedings of the 29th ACM International Conference on Information …, 2020 | 12 | 2020 |
| Dr. emotion: Disentangled representation learning for emotion analysis on social media to improve community resilience in the COVID-19 era and beyond M Ju, W Song, S Sun, Y Ye, Y Fan, S Hou, K Loparo, L Zhao Proceedings of the Web Conference 2021, 518-528, 2021 | 11 | 2021 |
| How Does Message Passing Improve Collaborative Filtering? M Ju, W Shiao, Z Guo, Y Ye, Y Liu, N Shah, T Zhao arXiv preprint arXiv:2404.08660, 2024 | 6 | 2024 |
| A multi-representation ensemble approach to classifying vocal diseases M Ju, Z Jiang, Y Chen, S Ray 2018 IEEE International Conference on Big Data (Big Data), 5258-5262, 2018 | 6 | 2018 |
| Exploring contrast consistency of open-domain question answering systems on minimally edited questions Z Zhang, W Yu, Z Ning, M Ju, M Jiang Transactions of the Association for Computational Linguistics 11, 1082-1096, 2023 | 3 | 2023 |
| MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation Z Zhang, Z Wang, T Ma, VS Taneja, S Nelson, NHL Le, K Murugesan, ... arXiv preprint arXiv:2412.08847, 2024 | 2 | 2024 |
| Robust training objectives improve embedding-based retrieval in industrial recommendation systems M Kolodner, M Ju, Z Fan, T Zhao, E Ghazizadeh, Y Wu, N Shah, Y Liu arXiv preprint arXiv:2409.14682, 2024 | 2 | 2024 |
Yanfang (Fanny) YeGalassi Family Collegiate Professor in Computer Science and Engineering, University of Notre Damend.edu의 이메일 확인됨