172 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Laboratoire d'Informatique Gaspard-MongeFR50 papers
- Centre National de la Recherche ScientifiqueFR42 papers
- Université Gustave EiffelFR32 papers
- UniLaSalle Amiens (ESIEE-Amiens)FR16 papers
- Pôle de recherche et d'enseignement supérieur Université Paris-EstFR13 papers
- École nationale des ponts et chausséesFR12 papers
- Université Paris-Est Marne-la-ValléeFR9 papers
- Paris-Est SupFR8 papers
- Laboratoire Interdisciplinaire des Énergies de DemainFR6 papers
- Université Paris CitéFR5 papers
- CentraleSupélecFR4 papers
- Laboratoire Bordelais de Recherche en InformatiqueFR4 papers
6 papers · 1 filter
Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention
Léo Hein, Giovanni de Nunzio, Giovanni Chierchia +2
Existing traffic volume estimation methods typically address either forecasting traffic on sensor-equipped roads or spatially imputing missing volumes using nearby sensors. While f…
Improving Plasticity in Online Continual Learning via Collaborative Learning
Maorong Wang, Nicolas Michel, Ling Xiao +1
Online Continual Learning (CL) solves the problem of learning the ever-emerging new classification tasks from a continuous data stream. Unlike its offline counterpart, in online CL…
Domain-Aware Augmentations for Unsupervised Online General Continual Learning
Nicolas Michel, Romain Negrel, Giovanni Chierchia +1
Continual Learning has been challenging, especially when dealing with unsupervised scenarios such as Unsupervised Online General Continual Learning (UOGCL), where the learning agen…
Learning Representations on the Unit Sphere: Investigating Angular Gaussian and von Mises-Fisher Distributions for Online Continual Learning
Nicolas Michel, Giovanni Chierchia, Romain Negrel +1
We use the maximum a posteriori estimation principle for learning representations distributed on the unit sphere. We propose to use the angular Gaussian distribution, which corresp…
Ultrametric Fitting by Gradient Descent
Giovanni Chierchia, Benjamin Perret
We study the problem of fitting an ultrametric distance to a dissimilarity graph in the context of hierarchical cluster analysis. Standard hierarchical clustering methods are speci…
Optimal Bounds on the VC-dimension
Monika Csikos, Andrey Kupavskii, Nabil H. Mustafa
The VC-dimension of a set system is a way to capture its complexity and has been a key parameter studied extensively in machine learning and geometry communities. In this paper, we…