{"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/generative-modeling-with-conditional","title":"Generative Modeling with Conditional Autoencoders: Building an Integrated Cell","arxiv_id":"1705.00092","date":"2017-04-28","proceeding":null,"authors":["Gregory R. Johnson","Rory M. Donovan-Maiye","Mary M. Maleckar"],"abstract":"We present a conditional generative model to learn variation in cell and\nnuclear morphology and the location of subcellular structures from microscopy\nimages. Our model generalizes to a wide range of subcellular localization and\nallows for a probabilistic interpretation of cell and nuclear morphology and\nstructure localization from fluorescence images. We demonstrate the\neffectiveness of our approach by producing photo-realistic cell images using\nour generative model. The conditional nature of the model provides the ability\nto predict the localization of unobserved structures given cell and nuclear\nmorphology.","url_abs":"http://arxiv.org/abs/1705.00092v1","url_pdf":"http://arxiv.org/pdf/1705.00092v1.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":"generative-modeling-with-conditional","repo_url":"https://github.com/AllenCellModeling/torch_integrated_cell","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"torch","reach":null},{"paper_slug":"generative-modeling-with-conditional","repo_url":"https://github.com/AllenCellModeling/pytorch_integrated_cell","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}