{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/molecular-generative-model-based-on","title":"Molecular generative model based on conditional variational autoencoder for de novo molecular design","arxiv_id":"1806.05805","date":"2018-06-15","proceeding":null,"authors":["Jaechang Lim","Seongok Ryu","Jin Woo Kim","Woo Youn Kim"],"abstract":"We propose a molecular generative model based on the conditional variational\nautoencoder for de novo molecular design. It is specialized to control multiple\nmolecular properties simultaneously by imposing them on a latent space. As a\nproof of concept, we demonstrate that it can be used to generate drug-like\nmolecules with five target properties. We were also able to adjust a single\nproperty without changing the others and to manipulate it beyond the range of\nthe dataset.","url_abs":"http://arxiv.org/abs/1806.05805v1","url_pdf":"http://arxiv.org/pdf/1806.05805v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"molecular-generative-model-based-on","repo_url":"https://github.com/jaechanglim/CVAE","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.05805","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}