Algorithms and calculus cover all theoretical and practical, software and hardware aspects of computer science. For a decade, artificial intelligence and learning have been concerned with the automatic design of algorithms and computational processes, guided by data, the expert, the user and/or the environment.
The main research axes of the department concern computational models and their robustness (from high-performance computing to quantum computing, including neural networks and distributed algorithms), processing architectures (graphs, distributed, synchronous or asynchronous processing), and methods (e.g., continuous, combinatorial, stochastic optimization; statistical learning and information theory). By construction, these research axes are the subject of collaborations with other departments, in particular Data Science and Fluid Mechanics-Energetics. The analysis and design of models and processes rely heavily on mathematical approaches (discrete and continuous, including probability, statistics and combinatorics) and statistical physics (in particular on the phase transition phenomena of complex systems), in conjunction with the LMO and CMAP (Maths and Maths. Appli), IJCLab (Physics), L2S (Signal Processing), as well as the LIX and the future LMF (Formal Methods) teams
Application areas include scientific computing (e.g., linear algebra, tensor calculus, numerical optimization, dynamical systems, simulation of quantum algorithms, computational mathematics and physics, systems of differential equations), distributed computing (e.g., cloud, scheduling, virtual currency, ubiquitous computing, autonomous robots, microbiological circuits), and data analysis.
Amanda Pelegrin Candemil, Hugo Gabrielidis, Filippo Gatti, Benjamin Salmon, Matheus Oliveira, et al.. Diagnostic performance of artefact-reduced cone-beam CT images using a generative adversarial neural network. Expert Systems with Applications, In press, 128907, ⟨10.1016/j.eswa.2025.128907⟩. ⟨hal-05157692⟩
Nicolas Atienza. Towards Reliable ML : Leveraging Multi-Modal Representations, Information Bottleneck and Extreme Value Theory. Machine Learning [stat.ML]. Université Paris-Saclay, 2025. English. ⟨NNT : 2025UPASG025⟩. ⟨tel-05140441⟩
Manon Blanc, Olivier Bournez. Quantifiying the robustness of dynamical systems. Relating time and space to length and precision. Computer Science Logic CSL’24, Feb 2024, Naples, Italy. pp.17:1-17:20, ⟨10.4230/lipics.csl.2024.17⟩. ⟨hal-04303119⟩
Djamel Eddine Amir, Benjamin Hellouin de Menibus. Minimality and computability of languages of G-shifts. ICALP 2025, Aarhus University, Jul 2025, Aarhus, Denmark. ⟨hal-05117426⟩
Pierre Fraigniaud, AmiArchitectures et modèles pour l'Interaction Paz, Sergio Rajsbaum. A speedup theorem for asynchronous computation with applications to consensus and approximate agreement. Distributed Computing, 2025, ⟨10.1007/s00446-025-00480-0⟩. ⟨hal-05114147⟩
Pierre Thomas Froidevaux, Alexandre Blondin-Massé, Chiara Marmo, Jérémy Neveu, Jean Privat, et al.. Travo. 2025, ⟨swh:1:dir:25c53be9cb372dca46dc311c114c9d961127225b;origin=https://gitlab.com/travo-cr/travo;visit=swh:1:snp:5f0faa62d3619f576a8a041c609ac66820f54a80;anchor=swh:1:rev:fd9302aab27cb93dc1ef24b3ab13a3da163564ca⟩. ⟨hal-05030605⟩
Felipe V. Furquim, Daniel Cordeiro, Valentin Dardilhac, Johanne Cohen. Characterizing Strategyproofness Through Score Functions in Voting Mechanisms. 2025. ⟨hal-05040764⟩
Julien Rauch, Damien Rontani, Stéphane Vialle. Data clustering on hybrid classical-quantum NISQ architecture with generative-based variational and parallel algorithms. Journal of Systems Architecture, In press, Special Issue on Architecture of Computing Systems Conference 2024, 165, pp.103431. ⟨10.1016/j.sysarc.2025.103431⟩. ⟨hal-05040633⟩
Guanlin He, Stéphane Vialle, Marc Baboulin. Generating Sparse Matrices for Large-scale Spectral Clustering on a Single GPU. International Journal of Parallel Programming, In press, 53 (4), pp.22. ⟨10.1007/s10766-025-00799-y⟩. ⟨hal-05040711⟩
Marc Baboulin, Oguz Kaya, Theo Mary, Matthieu Robeyns. Numerical stability of tree tensor network operations, and a stable rounding algorithm. 2025. ⟨hal-04996127⟩
Benjamin Hellouin de Menibus, Pacôme Perrotin. Subshifts Defined by Nondeterministic and Alternating Plane-walking Automata. 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025), Mar 2025, Iena, Germany. pp.56, ⟨10.4230/LIPIcs.STACS.2025.56⟩. ⟨hal-04951292⟩
Nicolas Atienza, Christophe Labreuche, Johanne Cohen, Michèle Sebag. Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach. ICLR 2025 – The Thirteenth International Conference on Learning Representations, Apr 2025, Singapore (SG), Singapore. ⟨hal-04922382⟩
Benjamin Hellouin de Menibus, Mathieu Sablik. Characterisation of sets of limit measures of a cellular automaton iterated on a random configuration. Ergodic Theory and Dynamical Systems, 2016, 38 (2), pp.601-650. ⟨10.1017/etds.2016.46⟩. ⟨hal-01299001⟩
Nathalie Aubrun, Julien Esnay, Mathieu Sablik. Domino Problem Under Horizontal Constraints. STACS 2020 37th International Symposium on Theoretical Aspects of Computer Science, 2020, Montpellier, France. ⟨10.4230/LIPIcs.STACS.2020.26⟩. ⟨hal-02380657⟩
Stijn Cambie, François Dross, Kolja Knauer, Xuan Hoang La, Petru Valicov. Partitions of planar (oriented) graphs into a connected acyclic and an independent set. 2024. ⟨hal-04840861⟩
Communication dans un congrès, Communication dans un congrès
Jędrzej Hodor, Xuan Hoang La, Piotr Micek, Clément Rambaud. Weak coloring numbers of minor-closed graph classes. ACM-SIAM Symposium on Discrete Algorithms (SODA25), Jan 2025, New Orleans, United States. pp.3325-3334, ⟨10.1137/1.9781611978322.107⟩. ⟨hal-04819269⟩