Results 51 to 60 of about 3,263,133 (311)
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs [PDF]
Computer Vision and Pattern Recognition, 2016 Deep learning has achieved a remarkable performance breakthrough in several fields, most notably in speech recognition, natural language processing, and computer vision.
Federico Monti +5 more
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Concepts and Practice of Statistics: Part 3 - Graphics
Australasian Orthodontic Journal, 1987 The process of analysis of a set data aims to detect patterns, especially relationships between variables, in the data. Statistical techniques can be described broadly as techniques to detect particular types of patterns, and to test whether such ...
McLean Alan L.
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Geometric aspects of 2-walk-regular graphs [PDF]
, 2013 A $t$-walk-regular graph is a graph for which the number of walks of given length between two vertices depends only on the distance between these two vertices, as long as this distance is at most $t$. Such graphs generalize distance-regular graphs and $t$
Cámara, Marc +3 more
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The Role of Visual Scaffolding in Enhancing Iranian EFL Students’ Writing Ability [PDF]
Issues in Language Teaching, 2019 To better illuminate the link between scaffolding and visual aids, this quasi-experimental study attempted to scaffold an intact group of 14 intermediate-level Iranian English as a foreign language (EFL) learners through providing graphs with the aim of ...
Mahnaz Mostafaei Alaei +2 more
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Embedding Graphs into Colored Graphs [PDF]
Transactions of the American Mathematical Society, 1988 If X X is a graph, κ \kappa a cardinal, then there is a graph Y Y such that if the vertex set of Y Y is κ \kappa -colored, then there exists a monocolored induced copy of X X ; moreover, if X X does not contain a complete graph on
Hajnal, András, Komjáth, P.
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Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs [PDF]
Computer Vision and Pattern Recognition, 2017 A number of problems can be formulated as prediction on graph-structured data. In this work, we generalize the convolution operator from regular grids to arbitrary graphs while avoiding the spectral domain, which allows us to handle graphs of varying ...
Martin Simonovsky, N. Komodakis
semanticscholar +1 more source
Classifying image analysis techniques from their output
International Journal of Computational Intelligence Systems, 2016 In this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not
C Guada +4 more
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Anomaly Detection in Graphs of Bank Transactions for Anti Money Laundering Applications
IEEE Access, 2022 Our aim in this paper is to detect bank clients involved in suspicious activities related to money laundering, using the graph of transactions of the bank.
Bogdan Dumitrescu +2 more
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Annals of Pure and Applied Logic, 2017 In two previous papers, we exposed a combinatorial approach to the program of Geometry of Interaction, a program initiated by Jean-Yves Girard. The strength of our approach lies in the fact that we interpret proofs by simpler structures - graphs - than Girard's constructions, while generalizing the latter since they can be recovered as special cases of
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Deep Learning on Graphs: A Survey [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2018 Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is non-trivial because of the unique characteristics of ...
Ziwei Zhang, Peng Cui, Wenwu Zhu
semanticscholar +1 more source