{"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/learning-latent-subspaces-in-variational","title":"Learning Latent Subspaces in Variational Autoencoders","arxiv_id":"1812.06190","date":"2018-12-14","proceeding":"NeurIPS 2018 12","authors":["Jack Klys","Jake Snell","Richard Zemel"],"abstract":"Variational autoencoders (VAEs) are widely used deep generative models\ncapable of learning unsupervised latent representations of data. Such\nrepresentations are often difficult to interpret or control. We consider the\nproblem of unsupervised learning of features correlated to specific labels in a\ndataset. We propose a VAE-based generative model which we show is capable of\nextracting features correlated to binary labels in the data and structuring it\nin a latent subspace which is easy to interpret. Our model, the Conditional\nSubspace VAE (CSVAE), uses mutual information minimization to learn a\nlow-dimensional latent subspace associated with each label that can easily be\ninspected and independently manipulated. We demonstrate the utility of the\nlearned representations for attribute manipulation tasks on both the Toronto\nFace and CelebA datasets.","url_abs":"http://arxiv.org/abs/1812.06190v1","url_pdf":"http://arxiv.org/pdf/1812.06190v1.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":"learning-latent-subspaces-in-variational","repo_url":"https://github.com/lipikaramaswamy/am207_final_project/blob/master/notebooks/csvae_swiss_roll.ipynb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1812.06190","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}