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Graphical Neural Networks (GNNs) are a class of neural networks designed to perform inference on data described by graphs.
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![]() Representation of Inorganic Synthesis Reactions and Prediction: Graphical Framework and Datasets Samuel Andrello Daniel Alabi Simon J. L. Billinge | |||
![]() Beyond the Hype: A Large-Scale Empirical Analysis of On-Chain Transactions in NFT Scams Wenkai Li Zongwei Li Xiaoqi Li Chunyi Zhang Xiaoyan Zhang Yuqing Zhang | |||
![]() Morphling: Fast, Fused, and Flexible GNN Training at Scale Anubhab Rupesh Nasre | |||
![]() Nonstabilizerness Estimation using Graph Neural Networks Vincenzo Lipardi Domenica Dibenedetto Georgios Stamoulis Evert van Nieuwenburg Mark H.M. Winands | |||
![]() D2D Power Allocation via Quantum Graph Neural NetworkInternational Conference on Mobile Computing and Ubiquitous Networking (ICMCUN), 2025 | |||
![]() FPGA or GPU? Analyzing comparative research for application-specific guidanceSoutheastCon (SoutheastCon), 2025 | |||
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