| How to certify machine learning based safety-critical systems? A systematic literature review F Tambon, G Laberge, L An, A Nikanjam, PSN Mindom, Y Pequignot, ... Automated Software Engineering 29 (2), 38, 2022 | 54 | 2022 |
| Silent bugs in deep learning frameworks: An empirical study of Keras and TensorFlow F Tambon, A Nikanjam, L An, F Khomh, G Antoniol Empirical Software Engineering 29 (1), 10, 2024 | 17 | 2024 |
| A probabilistic framework for mutation testing in deep neural networks F Tambon, F Khomh, G Antoniol Information and Software Technology 155, 107129, 2023 | 8 | 2023 |
| Bug characterization in machine learning-based systems MM Morovati, A Nikanjam, F Tambon, F Khomh, ZM Jiang Empirical Software Engineering 29 (1), 14, 2024 | 4 | 2024 |
| Bugs in large language models generated code F Tambon, AM Dakhel, A Nikanjam, F Khomh, MC Desmarais, G Antoniol arXiv preprint arXiv:2403.08937, 2024 | 2 | 2024 |
| Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends M Taraghi, G Dorcelus, A Foundjem, F Tambon, F Khomh arXiv preprint arXiv:2401.13177, 2024 | 2 | 2024 |
| Mutation testing of deep reinforcement learning based on real faults F Tambon, V Majdinasab, A Nikanjam, F Khomh, G Antoniol 2023 IEEE Conference on Software Testing, Verification and Validation (ICST …, 2023 | 2 | 2023 |
| Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study MM Morovati, F Tambon, M Taraghi, A Nikanjam, F Khomh arXiv preprint arXiv:2310.09575, 2023 | 1 | 2023 |
| GIST: Generated Inputs Sets Transferability in Deep Learning F Tambon, F Khomh, G Antoniol arXiv preprint arXiv:2311.00801, 2023 | | 2023 |
| HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks F Tambon, G Antoniol, F Khomh arXiv preprint arXiv:2107.04863, 2021 | | 2021 |
Foutse KhomhNSERC Arthur B. McDonald Fellow, Canada CIFAR AI Chair, FRQ-IVADO Chair, Full ProfessorDirección de correo verificada de polymtl.ca
