Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

标题
Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules
作者
关键词
-
出版物
Journal of Cheminformatics
Volume 14, Issue 1, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2022-10-17
DOI
10.1186/s13321-022-00652-1

向作者/读者发起求助以获取更多资源

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now