Correlated RNN Framework to Quickly Generate Molecules with Desired Properties for Energetic Materials in the Low Data Regime
Author:
Affiliation:
1. College of Computer Science, Sichuan University, Chengdu610064, China
2. College of Chemistry, Sichuan University, Chengdu610064, China
3. College of Management, Southwest University for Nationalities, Chengdu610041, China
Funder
Sichuan International Science and Technology Innovation Cooperation Project
Publisher
American Chemical Society (ACS)
Subject
Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c00997
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1. Inverse molecular design using machine learning: Generative models for matter engineering
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