Agenda

Département
Langue
Date
Thématique
2026

February

March

  • 11:00
    12:00

    Vincent Bridonneau (Université de Le Havre Normandie)

    Title: Generation and analysis of dynamic graphs

    Abstract:

    This work investigates iterative processes that generate sequences of graphs, with applications spanning complex network analysis and temporal graph theory. Given a seed configuration, such processes yield a continuous flow of graphs whose structural evolution raises fundamental questions. When no size constraints are imposed, under what conditions can we guarantee non-trivial long-term behavior? How do we rigorously characterize structural transitions between consecutive states? We address the first question by introducing the notion of sustainability, a framework for determining whether an iterative process admits periodic graph sequences. We propose and analyze a graph generator that illustrates the theoretical challenges inherent to this concept. For the second question, we develop a metric quantifying structural change across successive iterations. Together, these contributions open new avenues of inquiry and reinforce the interplay between complex network analysis and temporal graph theory.

    https://algodist.labri.fr/index.php/Main/GT

    English
    LaBRI 178
  • 12:45
    13:45

    The performance of mobility systems no longer relies solely on technology. AI, automation, hypervision, new uses: everywhere, the human factor is emerging as a key determinant of the safety, acceptability, and efficiency of transport services.

    During this scientific event, CATIE (Aquitaine Center for Information Technology and Electronics) https://www.catie.fr/language/fr/accueil/ will offer concrete feedback on how to integrate the human factor into the design of mobility systems and services. Using real-life cases from the aviation, rail, and road sectors, we will explore how analyzing behavior, physiological states, and human-system interactions can help us overcome the limitations of purely technological approaches.

    This session is aimed at researchers, doctoral students, and innovation stakeholders who want to better understand how the human factor can be integrated operationally into the design of tomorrow's mobility solutions.

    Speaker: Florian Larrue, Head of the Human-Centered Systems Department – CATIE

    Registration link.     

     

    Visio
  • 12:30
    13:00
    Café science ouverte

    Anna Loeff, Research Data Project Manager, Cross-functional Research Support Service (DIRDOC), will host a webinar.
    Presentation of the multidisciplinary national data warehouse Recherche Data Gouv, the institutional space of the University of Bordeaux, and details of the procedure for submitting and promoting your data.

    Registration.

    This short format (30 min) aims to raise awareness of the challenges and practices of open science among the entire Bordeaux university community, particularly researchers and doctoral students.
     

  • 14:00
    15:00

    In automated learning problems, the task is to find a model that maps given inputs to their corresponding outputs as accurately as possible. Over the past 30 years, machine learning and deep learning have achieved tremendous success in solving this type of problem. However, while the resulting models can be used to make predictions, they offer limited interpretability, i.e. they provide little insight into *how* they solve the problem. For instance, if we train a recurrent neural network to predict whether a sequence of events will lead to a crash, the model cannot describe the sequences of events that lead to crashes and provide solutions to remediate the issue. Program synthesis is a framework for solving learning problems with models that are programs in a domain-specific language, which allows creating interpretable models in the domain of the problem.

    In this talk, I will present an enumerative approach for learning Linear Temporal Logic (LTL) formulas from data. I will begin with an introduction to program synthesis, using examples from program de-obfuscation and anomaly explanation. In the second part, I will present the main techniques used in our algorithm: observational equivalence and domination, two pruning techniques used to reduce the search space, and a connection between LTL Learning and the Boolean Set Cover problem. Finally, I will discuss the engineering choices we made when implementing this algorithm in Bolt, an open-source tool available at https://github.com/SynthesisLab/Bolt.

    This talk is based on joint work with Nathanaël Fijalkow, Théo Matricon, Baptiste Mouillon and Pierre Vandenhove.

    English
    LaBRI

April