385 citations · 1.1k across the 45 of their papers we have counts for
7 papers · 1 filter
Contextual Semantic Interpretability
Diego Marcos, Ruth Fong, Sylvain Lobry +3
Convolutional neural networks (CNN) are known to learn an image representation that captures concepts relevant to the task, but do so in an implicit way that hampers model interpre…
Representation Transfer by Optimal Transport
Xuhong Li, Yves Grandvalet, Rémi Flamary +2
Learning generic representations with deep networks requires massive training samples and significant computer resources. To learn a new specific task, an important issue is to tra…
Optimal Transport for Conditional Domain Matching and Label Shift
Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso +3
We address the problem of unsupervised domain adaptation under the setting of generalized target shift (joint class-conditional and label shifts). For this framework, we theoretica…
A Cycle GAN Approach for Heterogeneous Domain Adaptation in Land Use Classification
Claire Voreiter, Jean-Christophe Burnel, Pierre Lassalle +3
In the field of remote sensing and more specifically in Earth Observation, new data are available every day, coming from different sensors. Leveraging on those data in classificati…
Time Series Alignment with Global Invariances
Titouan Vayer, Romain Tavenard, Laetitia Chapel +3
Multivariate time series are ubiquitous objects in signal processing. Measuring a distance or similarity between two such objects is of prime interest in a variety of applications,…
CO-Optimal Transport
Ievgen Redko, Titouan Vayer, Rémi Flamary +1
Optimal transport (OT) is a powerful geometric and probabilistic tool for finding correspondences and measuring similarity between two distributions. Yet, its original formulation…