| Deep generative modelling of aircraft trajectories in terminal maneuvering areas T Krauth, A Lafage, J Morio, X Olive, M Waltert Machine Learning with Applications 11, 100446, 2023 | 11 | 2023 |
| Synthetic aircraft trajectories generated with multivariate density models T Krauth, J Morio, X Olive, B Figuet, R Monstein Engineering Proceedings 13 (1), 7, 2021 | 10 | 2021 |
| A framework to evaluate aircraft trajectory generation methods X Olive, J Sun, MCR Murça, T Krauth Proceedings of the 14th USA/Europe Air Traffic Management Research and …, 2021 | 6 | 2021 |
| Quantitative air risk assessment for a drone inspection mission along fast train lines X Olive, P Le Blaye, L Sedov, T Krauth Air Traffic Management Research and Development Seminar (ATM) 2023, 2023 | 4 | 2023 |
| Large landing trajectory dataset for go-around analysis R Monstein, B Figuet, T Krauth, M Waltert, M Dettling Engineering Proceedings 28 (1), 2, 2022 | 4 | 2022 |
| Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling J Demange-Chryst, F Bachoc, J Morio, T Krauth arXiv preprint arXiv:2310.09194, 2023 | 2 | 2023 |
| Advanced collision risk estimation in terminal manoeuvring areas using a disentangled variational autoencoder for uncertainty quantification T Krauth, J Morio, X Olive, B Figuet Engineering Applications of Artificial Intelligence 133, 108137, 2024 | 1 | 2024 |
| Collision risk assessment in terminal manoeuvring areas based on trajectory generation methods T Krauth, B Figuet, X Olive, J Morio 15th Air Traffic Management Research and Development Seminar, Savannah, USA …, 2023 | 1 | 2023 |
