4.6k citations · 7.9k across the 144 of their papers we have counts for
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Knowledge-Distilled Graph Neural Networks for Personalized Epileptic Seizure Detection
Qinyue Zheng, Arun Venkitaraman, Simona Petravic +1
Wearable devices for seizure monitoring detection could significantly improve the quality of life of epileptic patients. However, existing solutions that mostly rely on full electr…
A Meta-GNN approach to personalized seizure detection and classification
Abdellah Rahmani, Arun Venkitaraman, Pascal Frossard
In this paper, we propose a personalized seizure detection and classification framework that quickly adapts to a specific patient from limited seizure samples. We achieve this by c…
Distributed Graph Learning with Smooth Data Priors
Isabela Cunha Maia Nobre, Mireille El Gheche, Pascal Frossard
Graph learning is often a necessary step in processing or representing structured data, when the underlying graph is not given explicitly. Graph learning is generally performed cen…
SafeAMC: Adversarial training for robust modulation recognition models
Javier Maroto, Gérôme Bovet, Pascal Frossard
In communication systems, there are many tasks, like modulation recognition, which rely on Deep Neural Networks (DNNs) models. However, these models have been shown to be susceptib…
On the benefits of robust models in modulation recognition
Javier Maroto, Gérôme Bovet, Pascal Frossard
Given the rapid changes in telecommunication systems and their higher dependence on artificial intelligence, it is increasingly important to have models that can perform well under…
Towards robust sensing for Autonomous Vehicles: An adversarial perspective
Apostolos Modas, Ricardo Sanchez-Matilla, Pascal Frossard +1
Autonomous Vehicles rely on accurate and robust sensor observations for safety critical decision-making in a variety of conditions. Fundamental building blocks of such systems are…