135 citations · 148 across the 8 of their papers we have counts for
8 papers · 1 filter
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov +4
Transformer-based architectures achieved breakthrough performance in natural language processing and computer vision, yet they remain inferior to simpler linear baselines in multiv…
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux
We propose a theoretical framework to analyze semi-supervised classification under the low density separation assumption in a high-dimensional regime. In particular, we introduce Q…
Knothe-Rosenblatt transport for Unsupervised Domain Adaptation
Aladin Virmaux, Illyyne Saffar, Jianfeng Zhang +1
Unsupervised domain adaptation (UDA) aims at exploiting related but different data sources to tackle a common task in a target domain. UDA remains a central yet challenging problem…
Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Attention based neural networks are state of the art in a large range of applications. However, their performance tends to degrade when the number of layers increases. In this work…
Improving Hierarchical Adversarial Robustness of Deep Neural Networks
Avery Ma, Aladin Virmaux, Kevin Scaman +1
Do all adversarial examples have the same consequences? An autonomous driving system misclassifying a pedestrian as a car may induce a far more dangerous -- and even potentially le…
Ego-based Entropy Measures for Structural Representations on Graphs
George Dasoulas, Giannis Nikolentzos, Kevin Scaman +2
Machine learning on graph-structured data has attracted high research interest due to the emergence of Graph Neural Networks (GNNs). Most of the proposed GNNs are based on the node…
Ego-based Entropy Measures for Structural Representations
George Dasoulas, Giannis Nikolentzos, Kevin Scaman +2
In complex networks, nodes that share similar structural characteristics often exhibit similar roles (e.g type of users in a social network or the hierarchical position of employee…
Coloring graph neural networks for node disambiguation
George Dasoulas, Ludovic Dos Santos, Kevin Scaman +1
In this paper, we show that a simple coloring scheme can improve, both theoretically and empirically, the expressive power of Message Passing Neural Networks(MPNNs). More specifica…