{"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/discriminative-regularization-for-generative","title":"Discriminative Regularization for Generative Models","arxiv_id":"1602.03220","date":"2016-02-09","proceeding":null,"authors":["Alex Lamb","Vincent Dumoulin","Aaron Courville"],"abstract":"We explore the question of whether the representations learned by classifiers\ncan be used to enhance the quality of generative models. Our conjecture is that\nlabels correspond to characteristics of natural data which are most salient to\nhumans: identity in faces, objects in images, and utterances in speech. We\npropose to take advantage of this by using the representations from\ndiscriminative classifiers to augment the objective function corresponding to a\ngenerative model. In particular we enhance the objective function of the\nvariational autoencoder, a popular generative model, with a discriminative\nregularization term. We show that enhancing the objective function in this way\nleads to samples that are clearer and have higher visual quality than the\nsamples from the standard variational autoencoders.","url_abs":"http://arxiv.org/abs/1602.03220v4","url_pdf":"http://arxiv.org/pdf/1602.03220v4.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":"discriminative-regularization-for-generative","repo_url":"https://github.com/vdumoulin/discgen","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"adam","method_name":"Adam"},{"method_slug":"batch-normalization","method_name":"Batch Normalization"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"discriminative-regularization","method_name":"Discriminative Regularization"}],"datasets_introduced":[],"methods_introduced":[{"slug":"discriminative-regularization","name":"Discriminative Regularization","full_name":"Discriminative Regularization"}],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}