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Found 4 papers, 2 papers with code
SADA: Semantic adversarial unsupervised domain adaptation for Temporal Action Localization
Temporal Action Localization (TAL) is a complex task that poses relevant challenges, particularly when attempting to generalize on new -- unseen -- domains in real-world applications.
IGNNITION: Bridging the Gap Between Graph Neural Networks and Networking Systems
In this article, we present IGNNITION, a novel open-source framework that enables fast prototyping of GNNs for networking systems.
Unveiling the potential of Graph Neural Networks for robust Intrusion Detection
To this end, we use a graph representation that keeps flow records and their relationships, and propose a novel Graph Neural Network (GNN) model tailored to process and learn from such graph-structured information.
The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks
During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in real-world deployments.
