MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previously proposed algorithms. All methods and datasets are integrated as parts of the open source DeepChem package(MIT license).
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Zhao Xu, Haiyang Yu, Jingtun Zhang, Yi Liu, Keqiang Yan, Bora Oztekin, Haoran Liu, Xuan Zhang, Cong Fu, Shuiwang Ji: DIG: A Turnkey Library for Diving into Graph Deep Learning Research (2021) arXiv
- Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, George Karypis: DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science (2021) arXiv
- Li, Ming; Ma, Zheng; Wang, Yu Guang; Zhuang, Xiaosheng: Fast Haar transforms for graph neural networks (2020)