Applying Graph Neural Networks to the Decision Version of Graph Combinatorial Optimization Problems حسب Raka Jovanovic (17947838)

"…<p dir="ltr">In recent years, there has been a significant increase in the application of graph neural networks on a wide range of different problems. …"

On the disk dimension of planar graphs حسب Abu-khzam, Faisal

"…Disk dimension finds application in circuit layout and related fields. For every fixed k, the family of ``yes'' instances is closed under minors and excludes a planar graph. …"
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Network Analysis and its Applications in Financial and Digital Assets حسب Almazloum, Ward

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Genetic and heuristic algorithms for regrouping service sites. (c2000) حسب Tabbara, Hiba

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Toward RDF normalization حسب Ticona-Herrera, Regina

"…Experimental tests show significant improvements, namely in reducing RDF description loading time and file size.…"
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Unsupervised knowledge representation of panoramic dental X-ray images using SVG image-and-object clustering حسب Salameh, Khouloud

"…Results underline our approach’s effectiveness, and its applicability in a practical application domain.…"
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Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations حسب Mansour, Nashat

"…It produces a significant reduction in execution time, which is necessary for their applicability to large problems.…"
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Enhancing fairness and scalability in IOTA tangle networks: a POMDP-based tip selection algorithm for decentralized systems حسب Mays Alshaikhli (22564811)

"…The Internet of Things Applications (IOTA) Tangle, a directed acyclic graph (DAG)-based structure, addresses these challenges by enabling scalable, feeless transactions for IoT applications. …"

The multi-parameterized cluster editing problem حسب Abu-Khzam, Faisal N.

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Improving text-to-image generation with object layout guidance حسب Jezia Zakraoui (14151399)

"…We then introduce an object layout module to capture the features of these objects from the corresponding scene graph. Specifically, the object layout module aggregates individual object features from the scene graph as well as averaged or likelihood object features generated by a graph convolutional neural network. …"