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Paul Almasan
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2020 – today
- 2024
- [b1]Paul Almasan:
Leveraging graph neural networks for optimization and traffic compression in network digital twins. Polytechnic University of Catalonia, Spain, 2024 - 2023
- [j6]José Suárez-Varela, Paul Almasan
, Miquel Ferriol Galmés
Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities. IEEE Netw. 37(3): 146-153 (2023) - [c7]Paul Almasan
Enhancing 5G Radio Planning with Graph Representations and Deep Learning. 5G-MeMZ@SIGCOMM 2023: 14-20 - [c6]Paul Almasan
Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks. GNNet@CoNEXT 2023: 1-6 - [i14]Paul Almasan, Krzysztof Rusek, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros:
Leveraging Spatial and Temporal Correlations for Network Traffic Compression. CoRR abs/2301.08962 (2023) - [i13]Paul Almasan, José Suárez-Varela, Andra Lutu, Albert Cabellos-Aparicio, Pere Barlet-Ros:
Enhancing 5G Radio Planning with Graph Representations and Deep Learning. CoRR abs/2309.03603 (2023) - [i12]Paul Almasan, Krzysztof Rusek, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros:
Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks. CoRR abs/2311.05337 (2023) - 2022
- [j5]Paul Almasan
Network Digital Twin: Context, Enabling Technologies, and Opportunities. IEEE Commun. Mag. 60(11): 22-27 (2022) - [j4]Paul Almasan
ENERO: Efficient real-time WAN routing optimization with Deep Reinforcement Learning. Comput. Networks 214: 109166 (2022) - [j3]Paul Almasan
Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case. Comput. Commun. 196: 184-194 (2022) - [c5]Krzysztof Rusek
Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing. CNSM 2022: 359-363 - [c4]Carlos Güemes-Palau, Paul Almasan
Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies. NOMS 2022: 1-5 - [i11]Paul Almasan, Miquel Ferriol Galmés, Jordi Paillisse, José Suárez-Varela, Diego Perino, Diego R. López, Antonio Agustin Pastor Perales, Paul Harvey, Laurent Ciavaglia, Leon Wong, Vishnu Ram, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros:
Digital Twin Network: Opportunities and Challenges. CoRR abs/2201.01144 (2022) - [i10]Carlos Güemes-Palau, Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio:
Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies. CoRR abs/2202.00360 (2022) - [i9]Paul Almasan, Miquel Ferriol Galmés
Network Digital Twin: Context, Enabling Technologies and Opportunities. CoRR abs/2205.14206 (2022) - [i8]Krzysztof Rusek, Paul Almasan, José Suárez-Varela, Piotr Cholda, Pere Barlet-Ros, Albert Cabellos-Aparicio:
Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing. CoRR abs/2209.10380 (2022) - 2021
- [j2]José Suárez-Varela
The graph neural networking challenge: a worldwide competition for education in AI/ML for networks. Comput. Commun. Rev. 51(3): 9-16 (2021) - [c3]Paul Almasan
Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges. HPSR 2021: 1-6 - [i7]Paul Almasan, José Suárez-Varela, Bo Wu, Shihan Xiao, Pere Barlet-Ros, Albert Cabellos-Aparicio:
Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges. CoRR abs/2106.09754 (2021) - [i6]José Suárez-Varela, Miquel Ferriol Galmés, Albert López, Paul Almasan, Guillermo Bernárdez, David Pujol-Perich, Krzysztof Rusek, Loïck Bonniot, Christoph Neumann, François Schnitzler, François Taïani, Martin Happ, Christian Maier, Jia Lei Du, Matthias Herlich
The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks. CoRR abs/2107.12433 (2021) - [i5]Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio:
ENERO: Efficient Real-Time Routing Optimization. CoRR abs/2109.10883 (2021) - [i4]José Suárez-Varela, Paul Almasan, Miquel Ferriol Galmés, Krzysztof Rusek, Fabien Geyer, Xiangle Cheng, Xiang Shi, Shihan Xiao, Franco Scarselli, Albert Cabellos-Aparicio, Pere Barlet-Ros:
Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities. CoRR abs/2112.14792 (2021) - 2020
- [j1]Krzysztof Rusek
RouteNet: Leveraging Graph Neural Networks for Network Modeling and Optimization in SDN. IEEE J. Sel. Areas Commun. 38(10): 2260-2270 (2020)
2010 – 2019
- 2019
- [c2]Arnau Badia-Sampera, José Suárez-Varela
Towards more realistic network models based on Graph Neural Networks. CoNEXT Companion 2019: 14-16 - [c1]José Suárez-Varela
Challenging the generalization capabilities of Graph Neural Networks for network modeling. SIGCOMM Posters and Demos 2019: 114-115 - [i3]Krzysztof Rusek, José Suárez-Varela, Paul Almasan, Pere Barlet-Ros, Albert Cabellos-Aparicio:
RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN. CoRR abs/1910.01508 (2019) - [i2]Paul Almasan, José Suárez-Varela, Arnau Badia-Sampera, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio:
Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case. CoRR abs/1910.07421 (2019) - 2018
- [i1]Paul Almasan, Jordi Paillisse, Alberto Rodríguez-Natal, Pere Barlet-Ros, Florin Coras, Vina Ermagan, Fabio Maino, Albert Cabellos-Aparicio:
Securing the Control-plane Channel and Cache of Pull-based ID/LOC Protocols. CoRR abs/1803.08568 (2018)
Coauthor Index
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last updated on 2024-08-16 18:30 CEST by the dblp team
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