{"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/informative-features-for-model-comparison","title":"Informative Features for Model Comparison","arxiv_id":"1810.11630","date":"2018-10-27","proceeding":"NeurIPS 2018 12","authors":["Wittawat Jitkrittum","Heishiro Kanagawa","Patsorn Sangkloy","James Hays","Bernhard Schölkopf","Arthur Gretton"],"abstract":"Given two candidate models, and a set of target observations, we address the\nproblem of measuring the relative goodness of fit of the two models. We propose\ntwo new statistical tests which are nonparametric, computationally efficient\n(runtime complexity is linear in the sample size), and interpretable. As a\nunique advantage, our tests can produce a set of examples (informative\nfeatures) indicating the regions in the data domain where one model fits\nsignificantly better than the other. In a real-world problem of comparing GAN\nmodels, the test power of our new test matches that of the state-of-the-art\ntest of relative goodness of fit, while being one order of magnitude faster.","url_abs":"http://arxiv.org/abs/1810.11630v1","url_pdf":"http://arxiv.org/pdf/1810.11630v1.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":"informative-features-for-model-comparison","repo_url":"https://github.com/wittawatj/kernel-mod","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"informative-features-for-model-comparison","repo_url":"https://github.com/jenninglim/model-comparison-test","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"informative-features-for-model-comparison","repo_url":"https://github.com/wittawatj/model-comparison-test","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}