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A Systematic Assessment of Deep Learning Models for Molecule Generation

arXiv 2008.09168 ↗First posted 20 Aug 2020cs.LG q-bio.QMcited by 3

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Abstract (arXiv)

In recent years the scientific community has devoted much effort in the development of deep learning models for the generation of new molecules with desirable properties (i.e. drugs). This has produced many proposals in literature. However, a systematic comparison among the different VAE methods is still missing. For this reason, we propose an extensive testbed for the evaluation of generative models for drug discovery, and we present the results obtained by many of the models proposed in literature.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Aug 2020.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 1.

3 papers.