| An empirical study towards characterizing deep learning development and deployment across different frameworks and platforms Q Guo, S Chen, X Xie, L Ma, Q Hu, H Liu, Y Liu, J Zhao, X Li ASE 2019, 2019 | 89 | 2019 |
| DeepMutation++: A mutation testing framework for deep learning systems Q Hu, L Ma, X Xie, B Yu, Y Liu, J Zhao ASE 2019, 2019 | 68 | 2019 |
| Towards characterizing adversarial defects of deep learning software from the lens of uncertainty X Zhang, X Xie, L Ma, X Du, Q Hu, Y Liu, J Zhao, M Sun ICSE 2020, 2020 | 55 | 2020 |
| Secure deep learning engineering: A software quality assurance perspective L Ma, F Juefei-Xu, M Xue, Q Hu, S Chen, B Li, Y Liu, J Zhao, J Yin, S See arXiv preprint arXiv:1810.04538, 2018 | 29 | 2018 |
| Deepgraph: A pycharm tool for visualizing and understanding deep learning models Q Hu, L Ma, J Zhao APSEC 2018, 2018 | 18 | 2018 |
| An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement Q Hu, Y Guo, M Cordy, X Xie, L Ma, M Papadakis, Y Le Traon TOSEM 2022, 2022 | 7 | 2022 |
| GraphCode2Vec: Generic Code Embedding via Lexical and Program Dependence Analyses W Ma, M Zhao, E Soremekun, Q Hu, J Zhang, M Papadakis, M Cordy, ... MSR 2022, 2021 | 5 | 2021 |
| Towards Exploring the Limitations of Active Learning: An Empirical Study Q Hu, Y Guo, M Cordy, X Xie, W Ma, M Papadakis, Y Le Traon ASE 2021, 2021 | 3 | 2021 |
| Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models Y Guo, Q Hu, M Cordy, M Papadakis, YL Traon CAIN 2022, 2021 | 1 | 2021 |
| MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles Y Guo, Q Hu, M Cordy, M Papadakis, YL Traon arXiv preprint arXiv:2109.12838, 2021 | 1 | 2021 |
| Is Self-Attention Powerful to Learn Code Syntax and Semantics? W Ma, M Zhao, X Xie, Q Hu, S Liu, J Zhang, W Wang, Y Liu arXiv preprint arXiv:2212.10017, 2022 | | 2022 |
| DRE: density-based data selection with entropy for adversarial-robust deep learning models Y Guo, Q Hu, M Cordy, M Papadakis, Y Le Traon Neural Computing and Applications, 1-18, 2022 | | 2022 |
| Enhancing Mixup-Based Graph Learning for Language Processing via Hybrid Pooling Z Dong, Q Hu, Y Guo, M Cordy, M Papadakis, YL Traon, J Zhao arXiv preprint arXiv:2210.03123, 2022 | | 2022 |
| Enhancing Code Classification by Mixup-Based Data Augmentation Z Dong, Q Hu, Y Guo, M Cordy, M Papadakis, YL Traon, J Zhao SANER 2023, 2022 | | 2022 |
| Efficient Testing of Deep Neural Networks via Decision Boundary Analysis Q Hu, Y Guo, X Xie, M Cordy, L Ma, M Papadakis, YL Traon ICSE 2023, 2022 | | 2022 |
| CodeS: A Distribution Shift Benchmark Dataset for Source Code Learning Q Hu, Y Guo, X Xie, M Cordy, L Ma, M Papadakis, YL Traon ICSE 2023 NIER, 2022 | | 2022 |
| Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment Q Hu, Y Guo, M Cordy, X Xie, W Ma, M Papadakis, YL Traon arXiv preprint arXiv:2204.04220, 2022 | | 2022 |
| LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing Q Hu, Y Guo, M Cordy, X Xie, M Papadakis, YL Traon arXiv preprint arXiv:2204.03994, 2022 | | 2022 |
Xiaofei XieSingapore Management UniversityVerified email at smu.edu.sg
