{"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-models-and-model-criticism-via","title":"Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy","arxiv_id":"1611.04488","date":"2016-11-14","proceeding":null,"authors":["Danica J. Sutherland","Hsiao-Yu Tung","Heiko Strathmann","Soumyajit De","Aaditya Ramdas","Alex Smola","Arthur Gretton"],"abstract":"We propose a method to optimize the representation and distinguishability of samples from two probability distributions, by maximizing the estimated power of a statistical test based on the maximum mean discrepancy (MMD). This optimized MMD is applied to the setting of unsupervised learning by generative adversarial networks (GAN), in which a model attempts to generate realistic samples, and a discriminator attempts to tell these apart from data samples. In this context, the MMD may be used in two roles: first, as a discriminator, either directly on the samples, or on features of the samples. Second, the MMD can be used to evaluate the performance of a generative model, by testing the model's samples against a reference data set. In the latter role, the optimized MMD is particularly helpful, as it gives an interpretable indication of how the model and data distributions differ, even in cases where individual model samples are not easily distinguished either by eye or by classifier.","url_abs":"https://arxiv.org/abs/1611.04488v6","url_pdf":"https://arxiv.org/pdf/1611.04488v6.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-models-and-model-criticism-via","repo_url":"https://github.com/dougalsutherland/opt-mmd","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1611.04488","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1611.04488"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/dougalsutherland/opt-mmd","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"summary":{"ran_violates":1,"unverified":9},"by_repo_kind":{"official":{"samples":10,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"e47297b1db7138e9","entry":"inverse_transform","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/utils.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/utils.py","link_basis":"harvester_set","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"e47297b1db7138e9"}},{"code_sha256_prefix":"cd4e6d34bb9ba789","entry":"binary_cross_entropy","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/ops.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/ops.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"cd4e6d34bb9ba789"}},{"code_sha256_prefix":"f0cb37d52c4b56e2","entry":"conv2d","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/ops.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/ops.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"f0cb37d52c4b56e2"}},{"code_sha256_prefix":"f62556c1124a15ae","entry":"conv_cond_concat","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/ops.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/ops.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"f62556c1124a15ae"}},{"code_sha256_prefix":"1bb085aab9eafe21","entry":"dot","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/tf_ops.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/tf_ops.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"1bb085aab9eafe21"}},{"code_sha256_prefix":"086f34a9a161bd00","entry":"merge","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/utils.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"086f34a9a161bd00"}},{"code_sha256_prefix":"d24c683b6cd29a6a","entry":"mix_rbf_mmd2","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/mmd.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/mmd.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"d24c683b6cd29a6a"}},{"code_sha256_prefix":"4075bf1103e8be13","entry":"rbf_mmd2","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/mmd.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/mmd.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"4075bf1103e8be13"}},{"code_sha256_prefix":"2f2d81eff705fc69","entry":"save_images","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/utils.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"2f2d81eff705fc69"}},{"code_sha256_prefix":"3b455641d13093a1","entry":"sq_sum","repo":"dougalsutherland/opt-mmd","repo_kind":"official","path":"gan/tf_ops.py","file_url":"https://github.com/dougalsutherland/opt-mmd/blob/HEAD/gan/tf_ops.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"3b455641d13093a1"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}