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pro vyhledávání: '"Kengkanna, Apakorn"'
Autor:
Kengkanna, Apakorn, Ohue, Masahito
Graph neural networks (GNNs) demonstrate great performance in compound property and activity prediction due to their capability to efficiently learn complex molecular graph structures. However, two main limitations persist including compound represen
Externí odkaz:
http://arxiv.org/abs/2304.06253
Autor:
Kengkanna, Apakorn1 (AUTHOR), Ohue, Masahito1 (AUTHOR) ohue@c.titech.ac.jp
Publikováno v:
Communications Chemistry. 4/5/2024, Vol. 7 Issue 1, p1-14. 14p.