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Conditional $\beta$-VAE for De Novo Molecular Generation. (arXiv:2205.01592v1 [q-bio.BM])
Web: http://arxiv.org/abs/2205.01592
May 4, 2022, 1:11 a.m. | Ryan J Richards, Austen M Groener
cs.LG updates on arXiv.org arxiv.org
Deep learning has significantly advanced and accelerated de novo molecular
generation. Generative networks, namely Variational Autoencoders (VAEs) can not
only randomly generate new molecules, but also alter molecular structures to
optimize specific chemical properties which are pivotal for drug-discovery.
While VAEs have been proposed and researched in the past for pharmaceutical
applications, they possess deficiencies which limit their ability to both
optimize properties and decode syntactically valid molecules. We present a
recurrent, conditional $\beta$-VAE which disentangles the latent space to …
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