Deep Latent-Variable Models for Controllable Molecule Generation
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)(2021)
摘要
Representation learning via deep generative models is opening a new avenue for small molecule generation in silico. Linking chemical and biological space remains a key challenge. In this paper, we debut a graph-based variational autoencoder framework to address this challenge under the umbrella of disentangled representation learning. The framework permits several inductive biases that connect the...
更多查看译文
关键词
Representation learning,Drugs,Biological system modeling,Conferences,Aerospace electronics,Benchmark testing,Bioinformatics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要