- 17/09/2021: Local Model-Agnostic Methods, Alexandre Reiffers-Masson [XAI reading group]
- 05/10/2021: Example-Based Explanations (Imen Ben-Amor, Univ. Avignon), and Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead (Antoine Caubrière, Univ. Avignon) [XAI reading group]
- 22/10/2021: Interpretability of Neural Networks, Robin DURAZ [XAI reading group]
- 15/12/2021, Andrea Moricetta (TU Wien), Explain-IT: Towards eXplainable AI for unsupervised network traffic analysis, , Conférence Invitée [XAI reading group]
- 10/03/2022, Nathan Dahlin (University of Southern California), Designing interpretable approximations to deep reinforcement learning with soft decision trees, Conférence Invitée [XAI reading group]
- 28/03/2022, Vincent Messié, A decentralized data layer for collaborative End-to-End service assurance, ICIN 2022 accepted paper
- 11/04/22, Sanaa Gandhi, Non-negative matrix factorization for network delay matrix completion, NOMS 2022 accepted paper (AnNet workshop)
- 12-13/05/22, Séminaire du département Informatique d'IMT Atlantique à Brignogan Plage
- 17/05/2022, Robin Duraz, Machine learning and visualization tools for cyberattack detection, RESSI 2022 accepted paper
- 18/05/2022, Stéphane Gosselin (Orange Innovation/Networks), Artificial Intelligence for Network Management -- a use case perspective [Machine Learning track @ IMT Atlantique]
- 23/05/2022, Minqi Wang, A MEC and UPF Compatible OLT for Time-Critical Mobile Services, ONDM 2022 Best Paper Award
- 25/02/2022, Julien Francq (Naval Group), Anomaly Detection using Machine Learning on Public ICS Datasets [Machine Learning track @ IMT Atlantique]
- 30/05/2022, Gugan Thoppe (Indian Institute of Science), Improving Sample Efficiency in Evolutionary Reinforcement Learning using Off-policy Ranking
- 31/05/2022 & 28/02/2023, Ziad Tlaiss, Troubleshooting enhancement with automated Slow-Start detection
- 09/06/2022, Lucas Drumetz, Handling stochasticity when learning dynamical systems from data