An empirical study of challenges in converting deep learning models M Openja, A Nikanjam, AH Yahmed, F Khomh, ZMJ Jiang 2022 IEEE International Conference on Software Maintenance and Evolution …, 2022 | 28 | 2022 |
Diverget: a search-based software testing approach for deep neural network quantization assessment AH Yahmed, HB Braiek, F Khomh, S Bouzidi, R Zaatour Empirical Software Engineering 27 (7), 193, 2022 | 9 | 2022 |
Deploying deep reinforcement learning systems: A taxonomy of challenges AH Yahmed, AA Abbassi, A Nikanjam, H Li, F Khomh 2023 IEEE International Conference on Software Maintenance and Evolution …, 2023 | 4 | 2023 |
Toward Debugging Deep Reinforcement Learning Programs with RLExplorer R Bouchoucha, AH Yahmed, D Patil, J Rajendran, A Nikanjam, ... 2024 IEEE International Conference on Software Maintenance and Evolution …, 2024 | | 2024 |
An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems AH Yahmed, R Bouchoucha, HB Braiek, F Khomh 2023 38th IEEE/ACM International Conference on Automated Software …, 2023 | | 2023 |
Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges A Haj Yahmed, A Allah Abbassi, A Nikanjam, H Li, F Khomh arXiv e-prints, arXiv: 2308.12438, 2023 | | 2023 |
Towards Reliable, Production-Ready Deep Learning and Deep Reinforcement Learning Systems A Haj Yahmed Polytechnique Montréal, 2023 | | 2023 |