1 citations · 1 across the 3 of their papers we have counts for
5 papers
Distillation of Weighted Automata from Recurrent Neural Networks using a Spectral Approach
Remi Eyraud, Stephane Ayache
This paper is an attempt to bridge the gap between deep learning and grammatical inference. Indeed, it provides an algorithm to extract a (stochastic) formal language from any recu…
Partial Trace Regression and Low-Rank Kraus Decomposition
Hachem Kadri, Stéphane Ayache, Riikka Huusari +2
The trace regression model, a direct extension of the well-studied linear regression model, allows one to map matrices to real-valued outputs. We here introduce an even more genera…
An AI-powered blood test to detect cancer using nanoDSF
Philipp O. Tsvetkov, Rémi Eyraud, Stéphane Ayache +12
We describe a novel cancer diagnostic method based on plasma denaturation profiles obtained by a non-conventional use of Differential Scanning Fluorimetry. We show that 84 glioma p…
Mapping individual differences in cortical architecture using multi-view representation learning
Akrem Sellami, François-Xavier Dupé, Bastien Cagna +4
In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable.…
Deep Networks with Adaptive Nyström Approximation
Luc Giffon, Stéphane Ayache, Thierry Artières +1
Recent work has focused on combining kernel methods and deep learning to exploit the best of the two approaches. Here, we introduce a new architecture of neural networks in which w…