Mathieu Galtier

According to our database, Mathieu Galtier authored at least 17 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Industry-Scale Orchestrated Federated Learning for Drug Discovery.

Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Wouter Heyndrickx, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Antoine Simon, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Collaborative Drug Discovery: Inference-level Data Protection Perspective.

Balazs Pejo, Mina Remeli, Adam Arany, Mathieu Galtier, Gergely Ács

Trans. Data Priv., 2022

Industry-Scale Orchestrated Federated Learning for Drug Discovery.

Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier

CoRR, 2022

2020

The future of digital health with federated learning.

Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletarì, Holger R. Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus H. Maier-Hein, Sébastien Ourselin, Micah J. Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso

npj Digit. Medicine, 2020

2019

Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning.

Mathieu N. Galtier, Camille Marini

CoRR, 2019

2018

Dendritic sodium spikes endow neurons with inverse firing rate response to correlated synaptic activity.

Tomasz Górski, Romain Veltz, Mathieu Galtier, Hélissande Fragnaud, Jennifer S. Goldman, Bartosz Telenczuk, Alain Destexhe

J. Comput. Neurosci., 2018

Domain adaptation with optimal transport improves EEG sleep stage classifiers.

Stanislas Chambon, Mathieu N. Galtier, Alexandre Gramfort

Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

2017

Morpheo: Traceable Machine Learning on Hidden data.

Mathieu Galtier, Camille Marini

CoRR, 2017

A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series.

Stanislas Chambon, Mathieu Galtier, Pierrick Arnal, Gilles Wainrib, Alexandre Gramfort

CoRR, 2017

2016

A local Echo State Property through the largest Lyapunov exponent.

Gilles Wainrib, Mathieu Galtier

Neural Networks, 2016

Slow feature analysis with spiking neurons and its application to audio stimuli.

Guillaume Bellec, Mathieu Galtier, Romain Brette, Pierre Yger

J. Comput. Neurosci., 2016

2015

Ideomotor feedback control in a recurrent neural network.

Mathieu Galtier

Biol. Cybern., 2015

2014

Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes.

Mathieu Galtier, Camille Marini, Gilles Wainrib, Herbert Jaeger

Neural Networks, 2014

2013

A Biological Gradient Descent for Prediction Through a Combination of STDP and Homeostatic Plasticity.

Mathieu Galtier, Gilles Wainrib

Neural Comput., 2013

2012

Hebbian Learning of Recurrent Connections: A Geometrical Perspective.

Mathieu Galtier, Olivier D. Faugeras, Paul C. Bressloff

Neural Comput., 2012

A combination of STDP, Hebbian learning and synaptic scaling deriving from a theoretical learning principle

Mathieu Galtier, Gilles Wainrib

CoRR, 2012

2011

A mathematical approach to unsupervised learning in recurrent neural networks. (Une approche mathématique de l'apprentissage non-supervisé dans les réseaux de neurones récurrents).

Mathieu Galtier

PhD thesis, 2011