| Anomaly detection for skin disease images using variational autoencoder Y Lu, P Xu arXiv preprint arXiv:1807.01349, 2018 | 94 | 2018 |
| Equivalence between dropout and data augmentation: A mathematical check D Zhao, G Yu, P Xu, M Luo Neural Networks 115, 82-89, 2019 | 31 | 2019 |
| The refinement of a Q-matrix: Assessing methods to validate tasks to skills mapping M Desmarais, B Beheshti, P Xu Educational Data Mining 2014, 2014 | 26 | 2014 |
| Combining Techniques to Refine Item to Skills Q-Matrices with a Partition Tree. MC Desmarais, P Xu, B Beheshti International Educational Data Mining Society, 2015 | 13 | 2015 |
| Boosted Decision Tree for Q-Matrix Refinement. P Xu, MC Desmarais International Educational Data Mining Society, 2016 | 11 | 2016 |
| An Empirical Research on Identifiability and Q-Matrix Design for DINA Model. P Xu, MC Desmarais International Educational Data Mining Society, 2018 | 5 | 2018 |
| –Methods to Refine the Mapping of Items to Skills MC Desmarais, P Xu Design Recommendations for Intelligent Tutoring Systems 39, 2018 | 1 | 2018 |
| Boosting Image Recognition with Non-differentiable Constraints X Li, Y Lu, P Xu, J Peng, C Desrosiers, X Liu arXiv preprint arXiv:1910.00736, 2019 | | 2019 |
| Q-matrix Refinement, Design and Derivation P Xu Ecole Polytechnique, Montreal (Canada), 2019 | | 2019 |
