MoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph-Reference-Cited by-同舟云学术

MoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph

Published:2021-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
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Author:

Sun Mengying¹,Xing Jing²,Wang Huijun³,Chen Bin²,Zhou Jiayu¹

Affiliation:

1. Michigan State University, East Lansing, MI, USA

2. Michigan State University, Grand Rapids, MI, USA

3. Agios Pharmaceuticals, Cambridge, MA, USA

Funder

National Science Foundation

Office of Naval Research

National Institute of Health

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3447548.3467186

Reference48 articles.

1. Yuki Markus Asano Christian Rupprecht and Andrea Vedaldi. 2019. Self-labelling via simultaneous clustering and representation learning. arXiv preprint arXiv:1911.05371(2019). Yuki Markus Asano Christian Rupprecht and Andrea Vedaldi. 2019. Self-labelling via simultaneous clustering and representation learning. arXiv preprint arXiv:1911.05371(2019).

2. Yunsheng Bai Hao Ding Yang Qiao Agustin Marinovic Ken Gu Ting Chen Yizhou Sun and Wei Wang. 2019. Unsupervised inductive whole-graph embed-ding by preserving graph proximity. (2019). Yunsheng Bai Hao Ding Yang Qiao Agustin Marinovic Ken Gu Ting Chen Yizhou Sun and Wei Wang. 2019. Unsupervised inductive whole-graph embed-ding by preserving graph proximity. (2019).

3. Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?

4. Large Scale Online Learning of Image Similarity through Ranking

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