Literatura académica sobre el tema "Graphe de connexions"
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Artículos de revistas sobre el tema "Graphe de connexions"
Bernard, Denis y Tony Jin. "Solution to the Quantum Symmetric Simple Exclusion Process: The Continuous Case". Communications in Mathematical Physics 384, n.º 2 (21 de abril de 2021): 1141–85. http://dx.doi.org/10.1007/s00220-021-04087-x.
Texto completoLeone, Antonella, Cristiano Longo, Carmela Gerardi y James E. Trosko. "Pro-Apoptotic Effect of Grape Seed Extract on MCF-7 Involves Transient Increase of Gap Junction Intercellular Communication and Cx43 Up-Regulation: A Mechanism of Chemoprevention". International Journal of Molecular Sciences 20, n.º 13 (2 de julio de 2019): 3244. http://dx.doi.org/10.3390/ijms20133244.
Texto completoCLAUZEL, Céline, Christophe EGGERT, Simon TARABON, Lili PASQUET, Gilles VUIDEL, Marion BAILLEUL, Claude MIAUD y Claire GODET. "Analyser la connectivité de la trame turquoise : définition, caractérisation et enjeux opérationnels". Sciences Eaux & Territoires, n.º 43 (16 de octubre de 2023): 67–71. http://dx.doi.org/10.20870/revue-set.2023.43.7642.
Texto completoIdris-Khodja, Noureddine, Paola Di Marco, Mona Farhat, Bernard Geny y Valérie B. Schini-Kerth. "Grape-Derived Polyphenols Prevent Doxorubicin-Induced Blunted EDH-Mediated Relaxations in the Rat Mesenteric Artery: Role of ROS and Angiotensin II". Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/516017.
Texto completoMitroshina, Elena V., Mikhail I. Krivonosov, Dmitriy E. Burmistrov, Maria O. Savyuk, Tatiana A. Mishchenko, Mikhail V. Ivanchenko y Maria V. Vedunova. "Signatures of the Consolidated Response of Astrocytes to Ischemic Factors In Vitro". International Journal of Molecular Sciences 21, n.º 21 (26 de octubre de 2020): 7952. http://dx.doi.org/10.3390/ijms21217952.
Texto completoLabai, Nadia y Johann Makowsky. "Tropical Graph Parameters". Discrete Mathematics & Theoretical Computer Science DMTCS Proceedings vol. AT,..., Proceedings (1 de enero de 2014). http://dx.doi.org/10.46298/dmtcs.2406.
Texto completoZhang, Yan X. "Adinkras for Mathematicians". Discrete Mathematics & Theoretical Computer Science DMTCS Proceedings vol. AS,..., Proceedings (1 de enero de 2013). http://dx.doi.org/10.46298/dmtcs.12826.
Texto completoBeazley, Elizabeth T. "Maximal Newton polygons via the quantum Bruhat graph". Discrete Mathematics & Theoretical Computer Science DMTCS Proceedings vol. AR,..., Proceedings (1 de enero de 2012). http://dx.doi.org/10.46298/dmtcs.3092.
Texto completoAusloos, Marcel. "God (≡ Elohim), The First Small World Network". Frontiers in Physics 10 (3 de junio de 2022). http://dx.doi.org/10.3389/fphy.2022.887752.
Texto completoBoussicault, Adrien. "Operations on partially ordered sets and rational identities of type A". Discrete Mathematics & Theoretical Computer Science Vol. 15 no. 2, Combinatorics (7 de abril de 2013). http://dx.doi.org/10.46298/dmtcs.595.
Texto completoTesis sobre el tema "Graphe de connexions"
Blouin, Baptiste. "Event extraction from facsimiles of ancient documents for history studies". Electronic Thesis or Diss., Aix-Marseille, 2022. http://www.theses.fr/2022AIXM0453.
Texto completoIn the current era of massive digitization of historical sources, the automatic extraction of events is a crucial step when dealing with historical texts. Event processing is an active area of research in the Natural Language Processing community, but resources and systems are mainly developed for processing contemporary texts.In this context, this thesis aims at automatically extracting events from historical documents.This thesis proposes multidisciplinary exchanges in order to adapt recent ontologies to historical research purposes.Beyond the specific needs of the digital humanities, OCRized historical documents ranging from more than a century are far from what contemporary approaches are used to deal with. Whether in terms of diachrony, quality or adaptation to the domain, the processing of this type of document poses major problems in NLP. We then suggest domain adaptation technics combining the use of recent specialized architectures and pre-processing steps, allowing to reduce the impact of these difficulties while taking advantage of contemporary resources.Finally, based on a recent paradigm consisting of translating tasks as a question and answer problem, we propose an event extraction pipeline suitable for processing historical documents. From the extraction of a word triggering an event in a sentence to a representation of more than a century of events in the form of graphs, we propose a targeted exploration of a large quantity of historical sources
Borouchaki, Houman. "Graphe de connexion et triangulation de delaunay". Paris 7, 1993. http://www.theses.fr/1993PA077127.
Texto completoLestrée, Laurent. "Recherche de mots et d'arbres en parallèle". Paris 7, 1993. http://www.theses.fr/1993PA077074.
Texto completoDavoine, Cécile. "Densification des connexions "flip-chip" grande surface : analyse de l'assemblage d'un détecteur infrarouge et mise au point d'une technologie innovante". Saint-Etienne, EMSE, 2006. http://www.theses.fr/2006EMSE0038.
Texto completoZini, Roger. "Placement, routage conjoints et hierarchiques de reseaux prediffuses". Paris 6, 1987. http://www.theses.fr/1987PA066116.
Texto completoDelbot, François. "Au delà de l'évaluation en pire cas : comparaison et évaluation en moyenne de processus d'optimisation pour le problème du vertex cover et des arbres de connexion de groupes dynamiques". Phd thesis, Université d'Evry-Val d'Essonne, 2009. http://tel.archives-ouvertes.fr/tel-00927315.
Texto completoKassel, Adrien. "Laplaciens des graphes sur les surfaces et applications à la physique statistique". Thesis, Paris 11, 2013. http://www.theses.fr/2013PA112101.
Texto completoWe study the determinant of the Laplacian on vector bundles on graphs and use it, combined with discrete complex analysis, to study models of statistical physics. We compute exact lattice constants, construct scaling limits for excursions of the loop-erased random walk on surfaces, and study some Gaussian fields and determinantal processes
Mondal, Kartick Chandra. "Algorithmes pour la fouille de données et la bio-informatique". Thesis, Nice, 2013. http://www.theses.fr/2013NICE4049.
Texto completoKnowledge pattern extraction is one of the major topics in the data mining and background knowledge integration domains. Out of several data mining techniques, association rule mining and bi-clustering are two major complementary tasks for these topics. These tasks gained much importance in many domains in recent years. However, no approach was proposed to perform them in one process. This poses the problems of resources required (memory, execution times and data accesses) to perform independent extractions and of the unification of the different results. We propose an original approach for extracting different categories of knowledge patterns while using minimum resources. This approach is based on the frequent closed patterns theoretical framework and uses a novel suffix-tree based data structure to extract conceptual minimal representations of association rules, bi-clusters and classification rules. These patterns extend the classical frameworks of association and classification rules, and bi-clusters as data objects supporting each pattern and hierarchical relationships between patterns are also extracted. This approach was applied to the analysis of HIV-1 and human protein-protein interaction data. Analyzing such inter-species protein interactions is a recent major challenge in computational biology. Databases integrating heterogeneous interaction information and biological background knowledge on proteins have been constructed. Experimental results show that the proposed approach can efficiently process these databases and that extracted conceptual patterns can help the understanding and analysis of the nature of relationships between interacting proteins
Lin, Zhouhan. "Deep neural networks for natural language processing and its acceleration". Thèse, 2019. http://hdl.handle.net/1866/23438.
Texto completoThis thesis by article consists of four articles which contribute to the field of deep learning, specifically in the acceleration of training through low-precision networks, and the application of deep neural networks on natural language processing. In the first article, we investigate a neural network training scheme that eliminates most of the floating-point multiplications. This approach consists of binarizing or ternarizing the weights in the forward propagation and quantizing the hidden states in the backward propagation, which converts multiplications to sign changes and binary shifts. Experimental results on datasets from small to medium size show that this approach result in even better performance than standard stochastic gradient descent training, paving the way to fast, hardware-friendly training of neural networks. In the second article, we proposed a structured self-attentive sentence embedding that extracts interpretable sentence representations in matrix form. We demonstrate improvements on 3 different tasks: author profiling, sentiment classification and textual entailment. Experimental results show that our model yields a significant performance gain compared to other sentence embedding methods in all of the 3 tasks. In the third article, we propose a hierarchical model with dynamical computation graph for sequential data that learns to construct a tree while reading the sequence. The model learns to create adaptive skip-connections that ease the learning of long-term dependencies through constructing recurrent cells in a recursive manner. The training of the network can either be supervised training by giving golden tree structures, or through reinforcement learning. We provide preliminary experiments in 3 different tasks: a novel Math Expression Evaluation (MEE) task, a well-known propositional logic task, and language modelling tasks. Experimental results show the potential of the proposed approach. In the fourth article, we propose a novel constituency parsing method with neural networks. The model predicts the parse tree structure by predicting a real valued scalar, named syntactic distance, for each split position in the input sentence. The order of the relative values of these syntactic distances then determine the parse tree structure by specifying the order in which the split points will be selected, recursively partitioning the input, in a top-down fashion. Our proposed approach was demonstrated with competitive performance on Penn Treebank dataset, and the state-of-the-art performance on Chinese Treebank dataset.
Capítulos de libros sobre el tema "Graphe de connexions"
Dijkstra, E. W. "A Note on Two Problems in Connexion with Graphs". En Edsger Wybe Dijkstra, 287–90. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3544585.3544600.
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