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1

DCH: A Deep Learning Approach To Universal Header Compressi..:

, In: Proceedings of the Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems,

Meslet-Millet, Fabien ; Mouysset, Sandrine ; Chaput, Emmanuel - p. 269-276 , 2023

Link: https://dl.acm.org/doi/1..

2

NeCSTGen: An approach for realistic network traffic generat..:

, In: GLOBECOM 2022 - 2022 IEEE Global Communications Conference,

Meslet-Millet, Fabien ; Mouysset, Sandrine ; Chaput, Emmanuel - p. 3108-3113 , 2022

Link: https://doi.org/10.1109/..

3

Deep learning for network traffic : classification, generat..:

Meslet-Millet, Fabien
NNT: 2023INPT0078. , 2023

Link: https://theses.hal.scien..

4

NeCSTGen: Realistic Network Traffic Generation using Deep L..:

Meslet-Millet, Fabien ; Mouysset, Sandrine ; Chaput, Emmanuel
hal-04080848. , 2023

Link: https://hal.science/hal-..

5

NeCSTGen: Realistic Network Traffic Generation using Deep L..:

Meslet-Millet, Fabien ; Mouysset, Sandrine ; Chaput, Emmanuel
hal-04080848. , 2023

Link: https://hal.science/hal-..

6

Deep learning for network traffic : classification, generat..:

Meslet-Millet, Fabien
NNT: 2023INPT0078. , 2023

Link: https://theses.hal.scien..

7

Apprentissage profond pour le trafic réseau : classificatio..:

Meslet-Millet, Fabien
http://www.theses.fr/2023INPT0078/document. , 2023

Link: http://www.theses.fr/202..

8

NeCSTGen: Realistic Network Traffic Generation using Deep L..:

Meslet-Millet, Fabien ; Mouysset, Sandrine ; Chaput, Emmanuel
hal-04080848. , 2023

Link: https://hal.science/hal-..

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