M2 next year

This page provide some information about the courses that will take place next year (2024-2025) in the Master 2 Computer Science Of ENSL.

CR01: Harnessing Inexactness in Scientific Computing, Elisa Riccietti (LIP) and Théo Mary (Lip6) https://perso.ens-lyon.fr/elisa.riccietti/coursM2.php   
CR02: Tensors and arithmetic circuits, from complexity theory to machine learning, par Pascal Koiran et Sébastien Tavenas https://docs.google.com/document/d/1pLq508s1a7m4FVXPL0yKFe7wYiaFsv2Xj4vmRh0kov8/edit?usp=sharing 
CR03: Robust discrete optimization, par Ayse Nur Arslan et Michaël Poss (Montpellier) https://aysnrarsln.github.io/rocourse.html
CR04: Numerical Linear Algebra, par Julien Langou (international Inria Chair, travaille avec Loic Marchal de Roma) https://langou.github.io/2023/12/11/langou-m2-fall2024.html 
CR05: Computational Optimal Transport for Machine and Deep Learning, par Mathurin Massias, Titouan Vayer et Quentin Bertrand https://mathurinm.github.io/otml.html or Learning with Differential Privacy, par Rémi Gribonval et Aurélien Garivier https://perso.ens-lyon.fr/aurelien.garivier/www.math.univ-toulouse.fr/_agarivie/DP.html
CR06: Virtualization technologies: Design and Implementation, Djob Mvondo (Rennes) and Alain Tchana (LIP) - https://gitlab.com/lenapster/ensl-cr03-virtualization

CR07:  Molecular programming: Theory & experiment, Nicolas Schabanel (LIP) http://perso.ens-lyon.fr/nicolas.schabanel/doku.php?id=lecturemolecularprogramming

CR08: Markov Decision Processes and Reinforcement Learning, Nicolas Gast and Bruno Gaujal (Inria Grenoble) https://team.inria.fr/polaris/markov-decision-processes-and-reinforcement-learning/

CR09: Machine learning for graphs and with graphs, Titouan Vayer (LIP) and Pierre Borgnat (LP) https://tvayer.github.io/courses/coursegraph.html
CR10:  Algorithms for public-key cryptography,  Guillaume Hanrot (LIP) and Benjamin Wesolowski (UMPA), http://perso.ens-lyon.fr/guillaume.hanrot/M2-2023-2024/proposal-2023-2024.html
CR11: Modern Algorithms for Symbolic Summation and Integration, Alin Bostan, Gilles Villard et Bruno Salvy https://mathexp.eu/bostan/AlgoSumInt/
CR12: Data-aware algorithms for matrix and tensor computations, Suraj Kumar (LIP) https://surakuma.github.io/courses/daamtc.html
CR13: Applied Lattice Cryptography, Alain Passelègue and Damien Stehlé (LIP) https://perso.ens-lyon.fr/alain.passelegue/teaching/m2_2023.html
CR14: Distributed algorithms for networks, Nicolas Bousquet, Laurent Feuilloley, Théo Pierron (LIRIS) https://perso.liris.cnrs.fr/nbousquet/Distributed/
CR15: Category theory for computer scientists, Le Thanh Dung (Tito) Nguyen (LIP) http://nguyentito.eu/categories.html
CR16 Approximation Theory and Proof Assistants: Certified Computations,  Damien Pous and Nicolas Brisebarre (LIP) https://perso.ens-lyon.fr/nicolas.brisebarre/M2R/CoqApprox/ 
CR17: Coalgebra: abstract tools for reasoning on state-based systems, Valeria Vignudelli and Damien Pous (LIP)
Year of study