This page provide some information about the courses that will take place next year (2025-2026) in the Master 2 Computer Science Of ENSL.
CR07: Floating-Point Arithmetic. Claude-Pierre Jeannerod (ARIC), Guillaume Melquiond (Toccata@inria, LMF, Saclay) , and Jean-Michel Muller (ARIC)
CR08: Independent Sets in Graphs. Édouard Bonnet, Jean-Florent Raymond, Stéphan Thomassé, Nicolas Trotignon and Rémi Watrigant (MC2) http://perso.ens-lyon.fr/stephan.thomasse/Independentsets.htm
CR09: Resource-aware computations on CPUs and GPUs. Suraj Kumar, Loris Marchal & Frédéric Vivien (ROMA) https://surakuma.github.io/courses/rac.html
CR10: Computer-assisted proofs. Daria Pchelina (MC2), Michael Rao (MC2), Damien Pous (Plume), Nathalie Revol (AriC) https://perso.ens-lyon.fr/daria.pchelina/cours_m2
CR11: Privacy-preserving machine learning with homomorphic encryption. Guillaume Hanrot (main), Jai Hyun Park, Alain Passelègue and Damien Stehlé (Cryptolab) https://perso.ens-lyon.fr/guillaume.hanrot/proposal-2025-2026.html
CR12: Graphs, Machines and Logic. Édouard Bonnet, Denis Kuperberg, Stéphan Thomassé, François Schwarzentruber (MC2)
https://perso.ens-lyon.fr/francois.schwarzentruber/teaching/m2-gml/
CR13: Algebraic and combinatorial aspects of category theory. Tom Hirschowitz https://hirschowitz.pages.math.cnrs.fr/teaching/cours-cat/
CR14: Embedded Audio Signal Processing. Tanguy Risset (Insa Lyon) et Romain Michon (GRAME-CNCM), Yann Orlarey https://inria-emeraude.github.io/son/
CR15: Reinforcement Learning and Bandits: beyond Average Return, Aurélien Garivier
CR16: Molecular programming: Theory & experiment, Nicolas Schabanel (LIP) http://perso.ens-lyon.fr/nicolas.schabanel/doku.php?id=lecturemolecularprogramming
Here is the list for last year (2024-2025):
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/
CR12: Data-aware algorithms for matrix and tensor computations, Suraj Kumar (LIP) https://surakuma.github.io/courses/daamtc.html