Benoit Gaüzère
Publications
Publications
Towards Spatio Temporal Graph Representations for Historical Spatial Data16th international conference on spatial information theory, 2024, Quebec (Canada), France. ⟨10.5281/zenodo.14713998⟩ |
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Insights on Using Graph Neural Networks for Sulcal Graphs Predictive Models14th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition (GbRPR 2025), Jun 2025, Caen, France. pp.79-89, ⟨10.1007/978-3-031-94139-9_8⟩ |
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A Differentiable Approximation of the Graph Edit DistanceStatistical Techniques in Pattern Recognition and Structural and Syntactic Pattern Recognition S+SSPR, Andrea Torsello; Luca Rossi; Filippo Bergamasco; Luca Cosmo, Sep 2024, Venise (IT), Italy |
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Bridging Distinct Spaces in Graph-based Machine Learning7th Asian Conference on Pattern Recognition (ACPR2023), Nov 2023, Kitakyushu, Japan. ⟨10.1007/978-3-031-47637-2_1⟩ |
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Maximal Independent Sets for Pooling in Graph Neural Networks13th IAPR-TC15 International Workshop on Graph-Based Representations in Pattern Recognition (GbR 2023), Sep 2023, Vietri Sul Mare, Italy. ⟨10.1007/978-3-031-42795-4_11⟩ |
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Graph Normalizing Flows to Pre-image Free Machine Learning for Regression13th IAPR-TC15 International Workshop on Graph-Based Representations in Pattern Recognition, Sep 2023, Salerno, Italy. ⟨10.1007/978-3-031-42795-4_9⟩ |
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Normalizing Flows pour éviter le problème de pré-imageGRETSI'23 : XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France |
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Ensemble de sommets indépendant maximal appliqué au pooling sur graphesCongrès Reconnaissance des Formes, Image, Apprentissage et Perception ( RFIAP), Jul 2022, VANNES, France |
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Normalizing Flow appliqué aux problèmes de pré-image de noyau24-ème Conférence d’Apprentissage automatique (CAp), Jul 2022, Vannes, France. pp.1-10 |
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A differentiable approximation for the Linear Sum Assignment Problem with Edition26th International Conference on Pattern Recognition, Aug 2022, Montréal, Canada |
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Maximal Independent Vertex Set applied to Graph PoolingStructural and Syntactic Pattern Recognition (SSPR), Aug 2022, Montréal, Canada |
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A Graph Pre-image Method Based on Graph Edit DistancesProceedings of IAPR Joint International Workshops on Statistical techniques in Pattern Recognition (SPR 2020) and Structural and Syntactic Pattern Recognition (SSPR 2020)., Jan 2021, Venise, Italy. ⟨10.1007/978-3-030-73973-7_21⟩ |
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Analyzing the Expressive Power of Graph Neural Networks in a Spectral PerspectiveProceedings of the International Conference on Learning Representations (ICLR), May 2021, Vienna, Austria |
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A Metric Learning Approach to Graph Edit Costs for RegressionProceedings of IAPR Joint International Workshops on Statistical techniques in Pattern Recognition (SPR 2020) and Structural and Syntactic Pattern Recognition (SSPR 2020), Jan 2021, Venise, Italy. ⟨10.1007/978-3-030-73973-7_23⟩ |
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Breaking the Limits of Message Passing Graph Neural NetworksProceedings of the 38th International Conference on Machine Learning (ICML), Jul 2021, Vienna, Austria. pp.599-608 |
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When Spectral Domain Meets Spatial Domain in Graph Neural NetworksThirty-seventh International Conference on Machine Learning (ICML 2020) - Workshop on Graph Representation Learning and Beyond (GRL+ 2020), Jul 2020, Vienna, Austria |
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Spectral-designed depthwise separable graph neural networksProceedings of Thirty-seventh International Conference on Machine Learning (ICML 2020) - Workshop on Graph Representation Learning and Beyond (GRL+ 2020), Jul 2020, Vienna, Austria |
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Generalized Median Graph via Iterative Alternate MinimizationsIAPR International workshop on Graph-Based Representation in Pattern Recognition, Donatello Conte, Jean-Yves Ramel,, Jun 2019, Tours, France. pp.99-109, ⟨10.1007/978-3-030-20081-7_10⟩ |
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Graph Neural Network for Symbol Detection on Document Images13th IAPR International Workshop on Graphics Recognition, Sep 2019, Sydney, Australia |
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Apprentissage profond pour l'approximation d'une distance d'édition entre graphesConférence sur l'Apprentissage Automatique, Jun 2018, Rouen, France |
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Approximate Graph Edit Distance by Several Local Searches in Parallel7th International Conference on Pattern Recognition Applications and Methods, Jan 2018, Funchal, Madeira, Portugal |
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A Hungarian Algorithm for Error-Correcting Graph Matching11th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition (GbRPR 2017), Pasquale Foggia, May 2017, AnaCapri, Italy. pp.118-127, ⟨10.1007/978-3-319-58961-9_11⟩ |
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Approximating Graph Edit Distance using GNCCPStructural, Syntactic, and Statistical Pattern Recognition, Nov 2016, Mérida, Mexico. pp.496--506 |
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Graph Edit Distance as a Quadratic ProgramICPR 2016 23rd International Conference on Pattern Recognition, Dec 2016, Cancun, Mexico |
Appariement d’ensembles avec édition : Application à la distance d’édition bipartie entre graphes20ème Congrès National sur la Reconnaissance des Formes et l'Intelligence Artificielle, Jun 2016, Clermont Ferrand, France |
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Human Tracking Using a Top-Down and Knowledge Based ApproachInternational Conference on Image Analysis and Processing, 2015, Genova, France. pp.257-267 |
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Semantic Web Technologies for Object Tracking and Video AnalyticsAdvances in Visual Computing, 2015, Las Vegas, United States. pp.574-585 |
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Approximate Graph Edit Distance Computation Combining Bipartite Matching and Exact Neighborhood Substructure DistanceGraph-Based Representation in Pattern Recognition, Cheng-Lin Liu ; Bin Luo; Walter G. Kropatsch; Jian Cheng, May 2015, Bejing, China. pp.188 - 197, ⟨10.1007/978-3-319-18224-7_19⟩ |
Human action recognition using an improved string edit distance2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Aug 2015, Karlsruhe, Germany. pp.1-6 |
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Graph kernel encoding substituents' relative positioningInternational Conference on Pattern Recognition (ICPR), Aug 2014, Stockholm, Sweden. 6 p |
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Approximate Graph Edit Distance Guided by Bipartite Matching of Bags of WalksStructural, Syntactic, and Statistical Pattern Recognition (S+SSPR),, Aug 2014, Joensuu, Finland. pp.73-82 |
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Représentation des cycles d'une molécule sous forme d'hypergrapheReconnaissance de Formes et Intelligence Artificielle (RFIA) 2014, Jun 2014, Rouen, France |
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A new hypergraph molecular representation6 ièmes Journées de la Chémoinformatique., Oct 2013, Nancy, France. pp.1 |
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A Comparison of Explicit and Implicit Graph Embedding Methods for Pattern Recognition9th IAPR - TC 15 workshop on Graph Based Repesentations in Pattern Recognition, May 2013, Vienne, Austria. pp.81 |
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Relevant Cycle Hypergraph Representation for Molecules9th IAPR-TC-15 Graph-Based Representations in Pattern Recognition, May 2013, Austria. pp.111 |
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Implicit and Explicit Graph Embedding: Comparison of both Approaches on Chemoinformatics ApplicationsJoint IAPR International Workshop, SSPR & SPR 2012, Nov 2012, Hiroshima, Japan. pp.510-518, ⟨10.1007/978-3-642-34166-3_56⟩ |
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Noyau de Treelets Appliqué aux Graphes ÉtiquetésRFIA 2012 (Reconnaissance des Formes et Intelligence Artificielle), Jan 2012, Lyon, France. pp.978-2-9539515-2-3 |
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Graph Kernels: Crossing Information from Different Patterns using Graph Edit DistanceJoint IAPR International Workshop, SSPR & SPR 2012, Nov 2012, Hiroshima, Japan. pp.42-50, ⟨10.1007/978-3-642-34166-3_5⟩ |
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Graph Kernels Based on Relevant Patterns and Cycle Information for ChemoinformaticsInternational Conference on Pattern Recognition (ICPR) 2012, Nov 2012, Tsukuba, Japan. pp.000-0000 |
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Shape Similarity based on Combinatorial Maps and a Tree Pattern Kernel21st International Conference on Pattern Recognition, Nov 2012, Tsukuba, Japan. pp.000-0000 |
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Two New Graph Kernels and Applications to Chemoinformatics8th IAPR-TC15 International Workshop, May 2011, Münster, Germany. pp.112, ⟨10.1007/978-3-642-20844-7⟩ |
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Deux nouveaux noyaux sur graphes et leurs applications en chimioinformatiqueCAp 2011 --- Conférence Francophone d'Apprentissage 2011, May 2011, Chambéry, France. pp.AGS 5 |
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Graph kernels in chemoinformaticsMatthias Dehmer and Frank Emmert-Streib. Quantitative Graph Theory Mathematical Foundations and Applications, CRC Press, pp.425-470, 2015, 978-1-4665-8451-8 |
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Graph Kernels in chemoinformaticsMatthias Dehmer and Frank Emmert-Streib. Quantitative Graph Theory: Mathematical Foundations and Applications, Taylor & Francis Group, 2014, 978-1-4665-8451-8 |
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Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks2020 |
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Graph Kernels Based on Linear Patterns: Theoretical and Experimental Comparisons2019 |
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A new Sinkhorn algorithm with Deletion and Insertion operations[Research Report] GREYC, UMR 6072. 2021 |
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A Quadratic Assignment Formulation of the Graph Edit Distance[Research Report] Normandie Université; GREYC CNRS UMR 6072; LITIS. 2015 |
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Relationships between Graph Edit Distance and Maximal Common Unlabeled Subgraph2012 |
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Application des méthodes à noyaux sur graphes pour la prédiction des propriétés des molécules.Chemo-informatique. Université de Caen, 2013. Français. ⟨NNT : ⟩ |