High-Performance Modeling and Optimization of Wireless Networks Using Bottleneck Structures by Aleix Torres-Camps, Alex Batlle Casellas, Yuyang Wang, Mauro Filomeno Rivero, Naga Bhushan, Jordi Ros-Giralt

“…Leveraging fast computational graph algorithms from the field of automatic differentiation such as backpropagation, these structures can solve certain wired network problems two to three orders of magnitude faster than traditional network simulators, without losing significant precision. …”
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TVGeAN: Tensor Visibility Graph-Enhanced Attention Network for Versatile Multivariant Time Series Learning Tasks by Mohammed Baz

“…TVGeAN consists of two new main components: TVG which extend the capabilities of visibility graph algorithms in representing MTSs by converting them into weighted temporal graphs where both the nodes and the edges are tensors. …”
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Detecting anomalies in graph networks on digital markets. by Agata Skorupka

“…It compares different graph algorithms to extract feature sets for anomaly detection models. …”
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PRCFX-DT: a new graph-based approach for feature selection and classification of genomic sequences by Amin Khodaei, Sania Eskandari, Hadi Sharifi, Behzad Mozaffari-Tazehkand

“…On the other hand, it has been demonstrated that the use of graph algorithms and machine learning in the analysis and examination of virus samples and even viral variants can yield beneficial results. …”
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INTEGRATED GRAPH-BASED TESTING PIPELINE FOR MODERN SINGLE-PAGE APPLICATIONS by Nataliia Golian, Varvara Tisheninova

“…., clicks, form submissions, navigation events). Leveraging graph algorithms, our approach automatically identifies missing paths to achieve exhaustive node, edge, and simple path coverage up to a configurable length, synthesizes minimal test sequences, and generates executable test scripts in frameworks such as Jest (unit / component), Cypress or Playwright (integration / E2E), and Postman (API). …”
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