Research Activities
My current research lies at the interface of graph-based representation of data and the definition of machine learning methods operating on graphs. In my recent works, I focused on:
- learning edit costs for graph edit distance
- improving pooling layers for GNN
- defining methods to alleviate the problem of the preimage of graphs
- applying graph-based machine learning methods to chemoinformatics
An up-to-date list of publications can be found on Google Scholar. All publications are available for download on HAL. If you still need any pdf, please drop me a mail.
Most of the papers have been implemented. Please check my GitHub. My ORCID record.
Projects
- FAMOUS: An ANR project on the definition of fair prediction models, with application on graphs. This project includes people from LIS, INT, Laboratoire Hubert Curien and EURONOVA.
- CodeGNN: ANR project focused on new contributions to Graph Neural Networks both on convolutions and pooling operators. Defining new GNN for temporal graphs is also an objective of this project.
- AGAC: Application des Graphes À la Chémoinformatique. A regional project with chemical scientists from COBRA to apply machine learning on graphs to chemical problematics.
- APi: Taming the Beast of the Preimage in Machine Learning for Structured Data: Signal, Image and Graph.
Students
I have co-advised the following PhD students:
- Stevan Stanovic (2021-2024): Apprentissage de la décimation de Graphes pour les GNN. This thesis aims to improve the pooling operator in graph neural networks.
- Clément Gledel (2020-2023): Preimage Problem for Graph Data. How can we use modern graph generation techniques to improve the computation of graph preimages.
- Linlin Jia (2017-2021): Machine learning and pattern recognition in chemoinformatics. Definition of methods based on graph representations for chemoinformatics. Led to a contribution on the learning of graph edit distance costs and a preimage method based on graph median.
- Guillaume Renton (2017-2021): Réseaux de Neurones sur Graphes : Analyse et Contributions. This thesis brought contributions to the analysis of spectral and spatial views of GNN convolutions, and defined a method to include edge information within the message passing framework.
Publications
2025
- Insights on Using Graph Neural Networks for Sulcal Graphs Predictive Models Alexis Imbert, Benoit Gaüzère, Sylvain Takerkart, Guillaume Auzias, Paul Honeine Graph-Based Representations in Pattern Recognition
- Pre-Image Free Graph Machine Learning with Normalizing Flows Clément Glédel, Benoît Gaüzère, Paul Honeine Pattern Recognition Letters
- Graph Neural Networks with Maximal Independent Set-Based Pooling: Mitigating over-Smoothing and over-Squashing Stevan Stanovic, Benoit Gaüzère, Luc Brun Pattern Recognition Letters
- A Differentiable Approximation of~the~Graph Edit Distance Julia Wallnig, Luc Brun, Benoit Gaüzère, Sébastien Bougleux, Florian Yger, David B. Blumenthal Structural, Syntactic, and Statistical Pattern Recognition
2023
- Graph Normalizing Flows to~Pre-image Free Machine Learning for~Regression Clément Glédel, Benoît Gaüzère, Paul Honeine Graph-Based Representations in Pattern Recognition
- Bridging Distinct Spaces in~Graph-Based Machine Learning Linlin Jia, Xiao Ning, Benoit Gaüzère, Paul Honeine, Kaspar Riesen Pattern Recognition
- Maximal Independent Sets for~Pooling in~Graph Neural Networks Stevan Stanovic, Benoit Gaüzère, Luc Brun Graph-Based Representations in Pattern Recognition
- Maximal Independent Vertex Set Applied to Graph Pooling Stevan Stanovic, Benoit Gaüzère, Luc Brun Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshops, S+ SSPR 2022, Montreal, QC, Canada, August 26–27, 2022, Proceedings
2022
- A Differentiable Approximation for the Linear Sum Assignment Problem with Edition Luc Brun, Benoit Gaüzere, Guillaume Renton, Sébastien Bougleux, Florian Yger 2022 26th International Conference on Pattern Recognition (ICPR)
- Normalizing Flow Appliqué Aux Problèmes de Pré-Image de Noyau Clément Glédel, Benoit Gaüzère, Paul Honeine 24-Ème Conférence d’Apprentissage Automatique (CAp)
- Graph Kernels Based on Linear Patterns: Theoretical and Experimental Comparisons Linlin Jia, Benoit Gaüzère, Paul Honeine Expert Systems with Applications
- Ensemble de Sommets Indépendant Maximal Appliqué Au Pooling Sur Graphes Stevan Stanovic, Benoit Gaüzère, Luc Brun Congrès Reconnaissance Des Formes, Image, Apprentissage et Perception (RFIAP)
2021
- Scalable Generalized Median Graph Estimation and Its Manifold Use in Bioinformatics, Clustering, Classification, and Indexing David B Blumenthal, Nicolas Boria, Sébastien Bougleux, Luc Brun, Johann Gamper, Benoit Gaüzère Information Systems
- Graphkit-Learn: A Python Library for Graph Kernels Based on Linear Patterns Linlin Jia, Benoit Gaüzère, Paul Honeine Pattern Recognition Letters
- A Graph Pre-image Method Based on Graph Edit Distances Linlin Jia, Benoit Gaüzère, Paul Honeine Proceedings of IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition (SPR 2020) and Structural and Syntactic Pattern Recognition (SSPR 2020).
- A Metric Learning Approach to Graph Edit Costs for Regression Linlin Jia, Benoit Gaüzère, Florian Yger, Paul Honeine Proceedings of IAPR Joint International Workshops on Statistical Techniques in Pattern Recognition (SPR 2020) and Structural and Syntactic Pattern Recognition (SSPR 2020)
- Symbols Detection and Classification Using Graph Neural Networks Guillaume Renton, Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Paul Honeine, Sébastien Adam Pattern Recognition Letters
2020
- Bridging the Gap between Spectral and Spatial Domains in Graph Neural Networks Muhammet Balcilar, Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sebastien Adam, Paul Honeine, Benoit Gauzere, Sebastien Adam, Paul Honeine
- Spectral-Designed Depthwise Separable Graph Neural Networks Muhammet Balcilar, Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sébastien Adam, Paul Honeine Proceedings of Thirty-seventh International Conference on Machine Learning (ICML 2020)-Workshop on Graph Representation Learning and Beyond (GRL+ 2020)
- Fast Linear Sum Assignment with Error-Correction and No Cost Constraints Sébastien Bougleux, Benoit Gaüzère, D.B. David B Blumenthal, Luc Brun Pattern Recognition Letters
- Predicting Experimental Electrophilicities from Quantum and Topological Descriptors: A Machine Learning Approach Guillaume Hoffmann, Muhammet Balcilar, Vincent Tognetti, Pierre Héroux, Benoit Beno\textbackslash\textasciicircum\textbackslash it Gaüzère, Sébastien Adam, Laurent Joubert Journal of Computational Chemistry
2019
- Generalized Median Graph via Iterative Alternate Minimizations Nicolas Boria, Sébastien Bougleux, Benoit Gaüzère, Luc Brun International Workshop on Graph-Based Representations in Pattern Recognition
- Graph Neural Network for Symbol Detection on Document Images Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sébastien Adam 13th IAPR International Workshop on Graphics Recognition, Sep 2019, Sydney, Australia
2018
- Approximate Graph Edit Distance by Several Local Searches in Parallel Évariste Daller, Sébastien Bougleux, Benoit Gaüzère, Luc Brun 7th International Conference on Pattern Recognition Applications and Methods
- Apprentissage Profond Pour l'approximation d'une Distance d'édition Entre Graphes Guillaume Renton, Benoit Gaüzère, Pierre Héroux, Sébastien Adam Conférence Sur l'Apprentissage Automatique
2017
- Graph Edit Distance Contest: Results and Future Challenges Zeina Abu-Aisheh, Benoit Gaüzere, Sébastien Bougleux, Jean-Yves Ramel, Luc Brun, Romain Raveaux, Pierre Héroux, Sébastien Adam Pattern Recognition Letters
- A Hungarian Algorithm for Error-Correcting Graph Matching Sébastien Bougleux, Benoit Gaüzère, Luc Brun International Workshop on Graph-Based Representations in Pattern Recognition
- Graph Edit Distance as a Quadratic Program S. Bougleux, Benoit Gaüzère, L. Brun Proceedings - International Conference on Pattern Recognition
2016
- Appariement d’ensembles Avec Édition: Application à La Distance d’édition Bipartie Entre Graphes Sébastien Bougleux, Benoit Gaüzère, Luc Brun RFIA
- Graph Edit Distance as a Quadratic Assignment Problem Sébastien Sebastien Bougleux, Luc Brun, Vincenzo Carletti, Pasquale Foggia, Benoit Gaüzère, Mario Vento Pattern Recognition Letters
- Approximating Graph Edit Distance Using GNCCP Benoit Gaüzère, Sébastien Bougleux, Luc Brun Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR)
2015
- Approximate Graph Edit Distance Computation Combining Bipartite Matching and Exact Neighborhood Substructure Distance Vincenzo Carletti, Benoit Gaüzère, Luc Brun, Mario Vento, Benoit Gaüzere, Luc Brun, Mario Vento International Workshop on Graph-Based Representations in Pattern Recognition
- Human Action Recognition Using an Improved String Edit Distance P. Foggia, Benoit Gaüzère, A. Saggese, M. Vento AVSS 2015 - 12th IEEE International Conference on Advanced Video and Signal Based Surveillance
- Semantic Web Technologies for Object Tracking and Video Analytics Benoit Gaüzère, Claudia Greco, Pierluigi Ritrovato, Alessia Saggese, Mario Vento International Symposium on Visual Computing, 2015
- Treelet Kernel Incorporating Cyclic, Stereo and Inter Pattern Information in Chemoinformatics Benoit Gaüzère, Pierre Anthony Grenier, Luc Brun, Didier Villemin Pattern Recognition
- Graph Kernels in Chemoinformatics Benoit Gaüzère, Luc Brun, Didier Villemin Quantitative Graph Theory: Mathematical Foundations and Applications
- Human Tracking Using a Top-Down and Knowledge Based Approach Benoit Gaüzère, Pierluigi Ritrovato, Alessia Saggese, Mario Vento Image Analysis and Processing—ICIAP 2015
2014
- Représentation Des Cycles d'une Molécule Sous Forme d'hypergraphe Benoit Gaüzère, Luc Brun, Didier Villemin Reconnaissance de Formes et Intelligence Artificielle (RFIA) 2014, Jun 2014
- Approximate Graph Edit Distance Guided by Bipartite Matching of Bags of Walks Benoit Gaüzère, Sébastien Bougleux, Kaspar Riesen, Luc Brun Structural, Syntactic, and Statistical Pattern Recognition
- Graph Kernel Encoding Substituents' Relative Positioning Benoit Gaüzère, Luc Brun, Didier Villemin Proceedings of International Conference on Pattern Recognition
2013
- A Comparison of Explicit and Implicit Graph Embedding Methods for Pattern Recognition Donatello Conte, Jean-Yves J.-Y. Ramel, Nicolas Sidere, M.M. Muhammad Muzzamil Luqman, Benoit Gaüzère, Jaume Gibert, Luc Brun, Mario Vento, N. Sidère, M.M. Muhammad Muzzamil Luqman, Benoit Gaüzère, Jaume Gibert, Luc Brun, Mario Vento International Workshop on Graph-Based Representations in Pattern Recognition
- A New Hypergraph Molecular Representation Benoit Gaüzère, Luc Brun, Didier Villemin 6 Ièmes Journées de La Chémoinformatique., Oct 2013, Nancy, France
- Noyau de Treelets Appliqué Aux Graphes Etiquetés et Aux Graphes de Cycles. Benoit Gaüzère, Luc Brun, Didier Villemin Revue d'Intelligence Artificielle
- Relevant Cycle Hypergraph Representation for Molecules Benoit Gaüzere, Luc Brun, Didier Villemin International Workshop on Graph-Based Representations in Pattern Recognition
2012
- Shape Similarity Based on Combinatorial Maps and a Tree Pattern Kernel S. Bougleux, F.-X. Dupe, L. Brun, Benoit Gaüzère, M. Mokhtari Proceedings - International Conference on Pattern Recognition
- Implicit and Explicit Graph Embedding: Comparison of Both Approaches on Chemoinformatics Applications Benoit Gaüzère, M. Hasegawa, L. Brun, S. Tabbone Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Graph Kernels: Crossing Information from Different Patterns Using Graph Edit Distance Benoit Gaüzère, Luc Brun, Didier Villemin Structural, Syntactic, and Statistical …
- Graph Kernels Based on Relevant Patterns and Cycle Information for Chemoinformatics Benoit Gaüzére, Luc Brun, Didier Villemin, Myriam Brun Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012)
- Noyau de Treelets Appliqué Aux Graphes Étiquetés Benoit Gaüzère, Luc Brun, Didier Villemin RFIA 2012 (Reconnaissance Des Formes et Intelligence Artificielle)
- Two New Graphs Kernels in Chemoinformatics Benoit Gaüzère, Luc Brun, Didier Villemin, Benoit Gaüzere, Luc Brun, Didier Villemin Pattern Recognition Letters
2011
- Two New Graph Kernels and Applications to Chemoinformatics Benoit Gaüzère, Luc Brun, Didier Villemin Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Deux Nouveaux Noyaux Sur Graphes et Leurs Applications En Chimioinformatique Benoit Gaüzère, Luc Brun, Didier Villemin CAp 2011---Conférence Francophone d'Apprentissage 2011
2025
- Towards Spatio Temporal Graph Representations for Historical Spatial Data Anne-Pauline Couteaud, Geraldine DEL MONDO, Benoit Gaüzère, Florent Hautefeuille, Clément Chatelain
2023
- Detecting Dynamic Patterns in Dynamic Graphs Using Subgraph Isomorphism Kamaldeep Singh Oberoi, Géraldine Del Mondo, Benoît Gaüzère, Yohan Dupuis, Pascal Vasseur Pattern Analysis and Applications
2022
- A Study on the Stability of Graph Edit Distance Heuristics Linlin Jia, Vincent Tognetti, Laurent Joubert, Benoit Gaüzère, Paul Honeine Electronics 2022, Vol. 11, Page 3312
2021
- Breaking the Limits of Message Passing Graph Neural Networks Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine Proceedings of the 38th International Conference on Machine Learning
- Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective Muhammet Balcilar, Renton Guillaume, Pierre Héroux, Benoit Gaüzère, Sébastien Adam, Paul Honeine