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While graph neural networks (GNNs) have gained popularity for learning circuit representations in various electronic design automation (EDA) tasks, they face challenges in scalability when applied to large graphs and exhibit limited generalizability
Externí odkaz:
http://arxiv.org/abs/2403.01317
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2021 Apr . 118(15), 1-3.
Externí odkaz:
https://www.jstor.org/stable/27040081