Academic literature on the topic 'Réseaux de Graphes avec Attention'
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Journal articles on the topic "Réseaux de Graphes avec Attention"
Díaz Villalba, Alejandro. "Comment outiller l’étude des autorités avec l’analyse de réseaux dans les grammaires françaises des XVIe et XVIIe siècles." SHS Web of Conferences 138 (2022): 03003. http://dx.doi.org/10.1051/shsconf/202213803003.
Full textBonnet, Nicolas. "Résilience d’un territoire face au chômage : les réseaux d’entreprises innovantes sur Montpellier." Nouvelles perspectives en sciences sociales 5, no. 1 (November 23, 2009): 97–115. http://dx.doi.org/10.7202/038625ar.
Full textVazquez, J., M. François, and D. Gilbert. "Gestion en temps réel d'un réseau d'assainissement : vérification de l'optimalité et de l'applicabilité de la théorie des graphes par rapport à la programmation linéaire mixte." Revue des sciences de l'eau 16, no. 4 (April 12, 2005): 425–42. http://dx.doi.org/10.7202/705516ar.
Full textVanderhaegen, Frédéric. "Pédagogie active et inclusive pour l’analyse de dangers de systèmes d’aide à la conduite basée sur la recherche de dissonances." J3eA 21 (2022): 2053. http://dx.doi.org/10.1051/j3ea/20222053.
Full textTHIERRY, Chloé, and Laure SANTONI. "Prise en compte des réseaux écologiques par les entreprises grâce à la modélisation de la connectivité avec Graphab." Sciences Eaux & Territoires, no. 46 (October 29, 2024): 8110. http://dx.doi.org/10.20870/revue-set.2024.46.8110.
Full textCLAUZEL, Céline, Christophe EGGERT, Simon TARABON, Lili PASQUET, Gilles VUIDEL, Marion BAILLEUL, Claude MIAUD, and Claire GODET. "Analyser la connectivité de la trame turquoise : définition, caractérisation et enjeux opérationnels." Sciences Eaux & Territoires, no. 43 (October 16, 2023): 67–71. http://dx.doi.org/10.20870/revue-set.2023.43.7642.
Full textGirard, Guillaume. "Représentation de la sexualité et des pratiques sexuelles à l’ère des réseaux sociaux dans Satyriasis : (mes années romantiques) de Guillaume Lambert." Voix Plurielles 15, no. 2 (December 9, 2018): 109–22. http://dx.doi.org/10.26522/vp.v15i2.2078.
Full textFoisy, Catherine. "Et si le salut venait aussi du Sud « missionné » ? Itinéraire de L’Entraide missionnaire (1950-1983)." Articles 79, no. 1 (March 18, 2013): 117–29. http://dx.doi.org/10.7202/1014857ar.
Full textCoulon, Damien. "Conflits, réseaux marchands et Consulats de mer en Catalogne à la fin du Moyen Âge." Réseaux, clientèles et associations dans les espaces hispaniques, no. 7 (October 20, 2022): 11–20. http://dx.doi.org/10.57086/sources.322.
Full textCrézégut, Anthony. "Sur une impossible histoire du marxisme à Paris : un monde éditorial français « provincialisé » ?" Actuel Marx 75, no. 1 (April 8, 2024): 149–67. http://dx.doi.org/10.3917/amx.075.0149.
Full textDissertations / Theses on the topic "Réseaux de Graphes avec Attention"
Amor, Yasmine. "Ιntelligent apprοach fοr trafic cοngestiοn predictiοn." Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMR129.
Full textTraffic congestion presents a critical challenge to urban areas, as the volume of vehicles continues to grow faster than the system’s overall capacity. This growth impacts economic activity, environmental sustainability, and overall quality of life. Although strategies for mitigating traffic congestion have seen improvements over the past few decades, many cities still struggle to manage it effectively. While various models have been developed to tackle this issue, existing approaches often fall short in providing real-time, localized predictions that can adapt to complex and dynamic traffic conditions. Most rely on fixed prediction horizons and lack the intelligent infrastructure needed for flexibility. This thesis addresses these gaps by proposing an intelligent, decentralized, infrastructure-based approach for traffic congestion estimation and prediction.We start by studying Traffic Estimation. We examine the possible congestion measures and data sources required for different contexts that may be studied. We establish a three-dimensional relationship between these axes. A rule-based system is developed to assist researchers and traffic operators in recommending the most appropriate congestion measures based on the specific context under study. We then proceed to Traffic Prediction, introducing our DECentralized COngestion esTimation and pRediction model using Intelligent Variable Message Signs (DECOTRIVMS). This infrastructure-based model employs intelligent Variable Message Signs (VMSs) to collect real-time traffic data and provide short-term congestion predictions with variable prediction horizons.We use Graph Attention Networks (GATs) due to their ability to capture complex relationships and handle graph-structured data. They are well-suited for modeling interactions between different road segments. In addition to GATs, we employ online learning methods, specifically, Stochastic Gradient Descent (SGD) and ADAptive GRAdient Descent (ADAGRAD). While these methods have been successfully used in various other domains, their application in traffic congestion prediction remains under-explored. In our thesis, we aim to bridge that gap by exploring their effectiveness within the context of real-time traffic congestion forecasting.Finally, we validate our model’s effectiveness through two case studies conducted in Muscat, Oman, and Rouen, France. A comprehensive comparative analysis is performed, evaluating various prediction techniques, including GATs, Graph Convolutional Networks (GCNs), SGD and ADAGRAD. The achieved results underscore the potential of DECOTRIVMS, demonstrating its potential for accurate and effective traffic congestion prediction across diverse urban contexts
Bertrand, Sébastien. "Optimisation de réseaux multiprotocoles avec encapsulation." Clermont-Ferrand 2, 2004. http://www.theses.fr/2004CLF21486.
Full textPoirier, Carl. "Assemblage d'ADN avec graphes de de Bruijn sur FPGA." Master's thesis, Université Laval, 2015. http://hdl.handle.net/20.500.11794/27132.
Full textJacob, Yann. "Classification dans les graphes hétérogènes et multi-relationnels avec contenu : Application aux réseaux sociaux." Paris 6, 2013. http://www.theses.fr/2013PA066494.
Full textThe emergence of the Web 2. 0 has seen the apparition of a large quantity of data that can easily be represented as complex graphs. There is many tasks of information analysis, prediction and retrieval on these data, while the state-of-the-art models are not adapted. In this thesis, we consider the task of node classification/labeling in complex partially labeled content networks. The applications for this task are for instance video/photo annotation in the Web 2. 0 websites, web spam detection or user labeling in social networks. The originality of our work is that we focus on two types of complex networks rarely considered in existing works: \textbf{multi-relationnal graphs} composed of multiple relation types and \textbf{heterogeneous networks} composed of multiple node types then of multiple joint labeling problems. First, we proposed two new algorithms for multi-relationnal graph labeling. These algorithms learn to weight the different relation types in the label propagation process according to their usefullness for the labeling task. They learn to combine the different relation types in an optimal manner for classification, while using the node content information. Then, we proposed an algorithm for heterogeneous graph labeling. Here, a specific problem is that each type of node has it own label set: for instance visual tags for a photo and groups for an user, then we must solve these different classification problems simultaneously using the graph structure. Our algorithm is based on the usage of a latent representation common to all node types allowing to process the different node types in an uniformized manner. Our experimental results show that this model is able to take in account the correlations between labels of different node types
Butelle, Franck. "Contribution à l'algorithmique distribuée de contrôle : arbres couvrants avec et sans contraintes." Paris 8, 1994. https://tel.archives-ouvertes.fr/tel-00082605.
Full textChopin, Morgan. "Problèmes d'optimisation avec propagation dans les graphes : complexité paramétrée et approximation." Phd thesis, Université Paris Dauphine - Paris IX, 2013. http://tel.archives-ouvertes.fr/tel-00933769.
Full textCarrillo, Hernan. "Colorisation d'images avec réseaux de neurones guidés par l'intéraction humaine." Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0016.
Full textColorization is the process of adding colors to grayscale images. It is an important task in the image-editing and animation community. Although automatic colorization methods exist, they often produce unsatisfying results due to artifacts such as color bleeding, inconsistency, unnatural colors, and the ill-posed nature of the problem. Manual intervention is often necessary to achieve the desired outcome. Consequently, there is a growing interest in automating the colorization process while allowing artists to transfer their own style and vision to the process. In this thesis, we investigate various interaction formats by guiding colors of specific areas of an image or transferring them from a reference image or object. As part of this research, we introduce two semi-automatic colorization frameworks. First, we describe a deep learning architecture for exemplar-based image colorization that takes into account user’s reference images. Our second framework uses a diffusion model to colorize line art using user-provided color scribbles. This thesis first delves into a comprehensive overview of state-of-the-art image colorization methods, color spaces, evaluation metrics, and losses. While recent colorization methods based on deep-learning techniques are achieving the best results on this task, these methods are based on complex architectures and a high number of joint losses, which makes the reasoning behind each of these methods difficult. Here, we leverage a simple architecture in order to analyze the impact of different color spaces and several losses. Then, we propose a novel attention layer based on superpixel features to establish robust correspondences between high-resolution deep features from target and reference image pairs, called super-attention. This proposal deals with the quadratic complexity problem of the non-local calculation in the attention layer. Additionally, it helps to overcome color bleeding artifacts. We study its use in color transfer and exemplar-based colorization. We finally extend this model to specifically guide the colorization on segmented objects. Finally, we propose a diffusion probabilistic model based on implicit and explicit conditioning mechanism, to learn colorizing line art. Our approach enables the incorporation of user guidance through explicit color hints while leveraging on the prior knowledge from the trained diffusion model. We condition with an application-specific encoder that learns to extract meaningful information on user-provided scribbles. The method generates diverse and high-quality colorized images
Pirayre, Aurélie. "Reconstruction et classification par optimisation dans des graphes avec à priori pour les réseaux de gènes et les images." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC1170/document.
Full textThe discovery of novel gene regulatory processes improves the understanding of cell phenotypicresponses to external stimuli for many biological applications, such as medicine, environmentor biotechnologies. To this purpose, transcriptomic data are generated and analyzed from mi-croarrays or more recently RNAseq experiments. For each gene of a studied organism placed indifferent living conditions, they consist in a sequence of genetic expression levels. From thesedata, gene regulation mechanisms can be recovered by revealing topological links encoded ingeometric graphs. In regulatory graphs, nodes correspond to genes. A link between two nodesis identified if a regulation relationship exists between the two corresponding genes. Such net-works are called Gene Regulatory Networks (GRNs). Their construction as well as their analysisremain challenging despite the large number of available inference methods.In this thesis, we propose to address this network inference problem with recently developedtechniques pertaining to graph optimization. Given all the pairwise gene regulation informa-tion available, we propose to determine the presence of edges in the final GRN by adoptingan energy optimization formulation integrating additional constraints. Either biological (infor-mation about gene interactions) or structural (information about node connectivity) a priorihave been considered to reduce the space of possible solutions. Different priors lead to differentproperties of the global cost function, for which various optimization strategies can be applied.The post-processing network refinements we proposed led to a software suite named BRANE for“Biologically-Related A priori for Network Enhancement”. For each of the proposed methodsBRANE Cut, BRANE Relax and BRANE Clust, our contributions are threefold: a priori-based for-mulation, design of the optimization strategy and validation (numerical and/or biological) onbenchmark datasets.In a ramification of this thesis, we slide from graph inference to more generic data processingsuch as inverse problems. We notably invest in HOGMep, a Bayesian-based approach using aVariation Bayesian Approximation framework for its resolution. This approach allows to jointlyperform reconstruction and clustering/segmentation tasks on multi-component data (for instancesignals or images). Its performance in a color image deconvolution context demonstrates bothquality of reconstruction and segmentation. A preliminary study in a medical data classificationcontext linking genotype and phenotype yields promising results for forthcoming bioinformaticsadaptations
Hizem, Mohamed Mejdi. "Recherche de chemins dans un graphe à pondérationdynamique : application à l'optimisation d'itinéraires dans les réseaux routiers." Phd thesis, Ecole Centrale de Lille, 2008. http://tel.archives-ouvertes.fr/tel-00344958.
Full textRoux, Marine. "Inférence de graphes par une procédure de test multiple avec application en Neuroimagerie." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT058/document.
Full textThis thesis is motivated by the analysis of the functional magnetic resonance imaging (fMRI). The need for methods to build such structures from fMRI data gives rise to exciting new challenges for mathematics. In this regards, the brain connectivity networks are modelized by a graph and we study some procedures that allow us to infer this graph.More precisely, we investigate the problem of the inference of the structure of an undirected graphical model by a multiple testing procedure. The structure induced by both the correlation and the partial correlation are considered. The statistical tests based on the latter are known to be highly dependent and we assume that they have an asymptotic Gaussian distribution. Within this framework, we study some multiple testing procedures that allow a control of false edges included in the inferred graph.First, we theoretically examine the False Discovery Rate (FDR) control of Benjamini and Hochberg’s procedure in Gaussian setting for non necessary positive dependent statistical tests. Then, we explore both the FDR and the Family Wise Error Rate (FWER) control in asymptotic Gaussian setting. We present some multiple testing procedures, well-suited for correlation (resp. partial correlation) tests, which provide an asymptotic control of the FWER. Furthermore, some first theoretical results regarding asymptotic FDR control are established.Second, the properties of the multiple testing procedures that asymptotically control the FWER are illustrated on a simulation study, for statistical tests based on correlation. We finally conclude with the extraction of cerebral connectivity networks on real data set
Book chapters on the topic "Réseaux de Graphes avec Attention"
GUYOMAR, Cervin, and Claire LEMAITRE. "Métagénomique et métatranscriptomique." In Des séquences aux graphes, 151–86. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9066.ch5.
Full textConference papers on the topic "Réseaux de Graphes avec Attention"
Quintas, Sebastião, Alberto Abad, Julie Mauclair, Virginie Woisard, and Julien Pinquier. "Utilisation de réseaux de neurones profonds avec attention pour la prédiction de l’intelligibilité de la parole de patients atteints de cancers ORL." In XXXIVe Journées d'Études sur la Parole -- JEP 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/jep.2022-7.
Full textCojocaru, Mariana. "Research on the conformity of labels of foods marketed in the Republic of Moldova." In Simpozion stiintific al tinerilor cercetatori, editia 20. Academy of Economic Studies of Moldova, 2023. http://dx.doi.org/10.53486/9789975359023.27.
Full textReports on the topic "Réseaux de Graphes avec Attention"
Hilbrecht, Margo, and Norah Keating. Tendances en matière de migration et d’urbanisation en lien avec le bien-être des familles au Canada : Regard sur l’incapacité et les questions autochtones. The Vanier Institute of the Family, December 2022. http://dx.doi.org/10.61959/q220119a.
Full textGruson-Daniel, Célya, and Maya Anderson-González. Étude exploratoire sur la « recherche sur la recherche » : acteurs et approches. Ministère de l'enseignement supérieur et de la recherche, November 2021. http://dx.doi.org/10.52949/24.
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