| Techniques for interpretable machine learning M Du, N Liu, X Hu Communications of the ACM 63 (1), 68-77, 2019 | 396 | 2019 |
| Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks H Wang, Z Wang, M Du, F Yang, Z Zhang, S Ding, P Mardziel, X Hu CVPR Workshop on Fair, Data-Efficient and Trusted Computer Vision, 2020 | 122* | 2020 |
| Towards explanation of dnn-based prediction with guided feature inversion M Du, N Liu, Q Song, X Hu KDD, 2018 | 75 | 2018 |
| Fairness in deep learning: A computational perspective M Du, F Yang, N Zou, X Hu IEEE Intelligent Systems, 2020 | 46 | 2020 |
| XFake: explainable fake news detector with visualizations F Yang, SK Pentyala, S Mohseni, M Du, H Yuan, R Linder, ED Ragan, S Ji, ... The Web Conference (WWW), 2019 | 41 | 2019 |
| Evaluating explanation without ground truth in interpretable machine learning F Yang, M Du, X Hu arXiv preprint arXiv:1907.06831, 2019 | 35 | 2019 |
| Specae: Spectral autoencoder for anomaly detection in attributed networks Y Li, X Huang, J Li, M Du, N Zou CIKM, 2019 | 29* | 2019 |
| Towards generalizable forgery detection with locality-aware autoencoder M Du, S Pentyala, Y Li, X Hu CIKM, 2019 | 29* | 2019 |
| On attribution of recurrent neural network predictions via additive decomposition M Du, N Liu, F Yang, S Ji, X Hu The Web Conference (WWW), 2019 | 25 | 2019 |
| An embarrassingly simple approach for trojan attack in deep neural networks R Tang, M Du, N Liu, F Yang, X Hu ACM International Conference on Knowledge Discovery & Data Mining (KDD）, 2020 | 20 | 2020 |
| Learning Credible Deep Neural Networks with Rationale Regularization M Du, N Liu, F Yang, X Hu IEEE International Conference on Data Mining (ICDM), 2019 | 18* | 2019 |
| Representation interpretation with spatial encoding and multimodal analytics N Liu, M Du, X Hu ACM International Conference on Web Search and Data Mining (WSDM), 2019 | 11 | 2019 |
| Deep Structured Cross-Modal Anomaly Detection Y Li, N Liu, J Li, M Du, X Hu International Joint Conference on Neural Networks (IJCNN), 2019 | 10* | 2019 |
| Supervised training and contextually guided salient object detection M Du, X Wu, W Chen, Z Li Digital Signal Processing, 2017 | 7 | 2017 |
| Adversarial machine learning: An interpretation perspective N Liu, M Du, X Hu SIGKDD Explorations, 2020 | 6* | 2020 |
| Salient object detection via region contrast and graph regularization X Wu, M Du, W Chen, J Wang Science China Information Sciences, 2016 | 6 | 2016 |
| Mitigating Gender Bias in Captioning Systems R Tang, M Du, Y Li, Z Liu, X Hu The Web Conference (WWW), 2020 | 5* | 2020 |
| Exploiting multiple contexts for saliency detection M Du, X Wu, W Chen, J Wang Journal of Electronic Imaging, 2016 | 5 | 2016 |
| Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models M Du, V Manjunatha, R Jain, R Deshpande, F Dernoncourt, J Gu, T Sun, ... NAACL 2021, 2021 | 4 | 2021 |
| Social media and psychological disorder NH Ismail, M Du, X Hu Social Web and Health Research, 171-192, 2019 | 4 | 2019 |
Xia "Ben" HuAssociate Professor of Computer Science, Rice UniversityVerified email at rice.edu
