Camille Marini

According to our database, Camille Marini authored at least 7 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• 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

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

2019

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

Mathieu N. Galtier, Camille Marini

CoRR, 2019

2017

Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy.

Laetitia Le, Camille Marini, Alexandre Gramfort, David Nguyen, Mehdi Cherti, Sana Tfaili, Ali Tfayli, Arlette Baillet-Guffroy, Patrice Prognon, Pierre Chaminade, Eric Caudron, Balázs Kégl

CoRR, 2017

Morpheo: Traceable Machine Learning on Hidden data.

Mathieu Galtier, Camille Marini

CoRR, 2017

2014

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

Mathieu Galtier, Camille Marini, Gilles Wainrib, Herbert Jaeger

Neural Networks, 2014

Towards Prospective Life Cycle Assessment: How to Identify Key Parameters Inducing Most Uncertainties in the Future? Application to Photovoltaic Systems Installed in Spain.

Camille Marini, Isabelle Blanc

Proceedings of the Computational Science and Its Applications - ICCSA 2014 - 14th International Conference, Guimarães, Portugal, June 30, 2014