{"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-adversarial-interpolative","title":"Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions","arxiv_id":"1807.06650","date":"2018-07-17","proceeding":null,"authors":["Tim Sainburg","Marvin Thielk","Brad Theilman","Benjamin Migliori","Timothy Gentner"],"abstract":"We present a neural network architecture based upon the Autoencoder (AE) and\nGenerative Adversarial Network (GAN) that promotes a convex latent distribution\nby training adversarially on latent space interpolations. By using an AE as\nboth the generator and discriminator of a GAN, we pass a pixel-wise error\nfunction across the discriminator, yielding an AE which produces non-blurry\nsamples that match both high- and low-level features of the original images.\nInterpolations between images in this space remain within the latent-space\ndistribution of real images as trained by the discriminator, and therfore\npreserve realistic resemblances to the network inputs. Code available at\nhttps://github.com/timsainb/GAIA","url_abs":"http://arxiv.org/abs/1807.06650v3","url_pdf":"http://arxiv.org/pdf/1807.06650v3.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-adversarial-interpolative","repo_url":"https://github.com/timsainb/GAIA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"}],"methods":[{"method_slug":"ae","method_name":"AE"},{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1807.06650","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}