{"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/multi-objective-deep-data-generation-with","title":"Multi-objective Deep Data Generation with Correlated Property Control","arxiv_id":"2210.01796","date":"2022-10-01","proceeding":null,"authors":["Shiyu Wang","Xiaojie Guo","Xuanyang Lin","Bo Pan","Yuanqi Du","Yinkai Wang","Yanfang Ye","Ashley Ann Petersen","Austin Leitgeb","Saleh AlKhalifa","Kevin Minbiole","William Wuest","Amarda Shehu","Liang Zhao"],"abstract":"Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular design. However, the advancement of deep generative models is limited by challenges to generate objects that possess multiple desired properties: 1) the existence of complex correlation among real-world properties is common but hard to identify; 2) controlling individual property enforces an implicit partially control of its correlated properties, which is difficult to model; 3) controlling multiple properties under various manners simultaneously is hard and under-explored. We address these challenges by proposing a novel deep generative framework that recovers semantics and the correlation of properties through disentangled latent vectors. The correlation is handled via an explainable mask pooling layer, and properties are precisely retained by generated objects via the mutual dependence between latent vectors and properties. Our generative model preserves properties of interest while handling correlation and conflicts of properties under a multi-objective optimization framework. The experiments demonstrate our model's superior performance in generating data with desired properties.","url_abs":"https://arxiv.org/abs/2210.01796v3","url_pdf":"https://arxiv.org/pdf/2210.01796v3.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":"multi-objective-deep-data-generation-with","repo_url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-generation","task_name":"Image Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2210.01796","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.01796"}},"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":"deterministic:regex_extraction","url":"https://github.com/shi-yu-wang/CorrVAE","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae","reach":null}],"summary":{"ran":2,"ran_draft_wrong":2,"ran_honours":3,"unverified":3},"by_repo_kind":{"listed":{"samples":5,"ran":4,"repositories":1},"found_in_text":{"samples":5,"ran":3,"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":10,"samples":[{"code_sha256_prefix":"f8c46729447abf96","entry":"ControlVAE","repo":"karolrogozinski/cern_alice_fast_sim_corrvae","repo_kind":"listed","path":"src/model.py","file_url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae/blob/HEAD/src/model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f8c46729447abf96"}},{"code_sha256_prefix":"c48a1f23f5a0b852","entry":"ControlVAE","repo":"shi-yu-wang/CorrVAE","repo_kind":"found_in_text","path":"disvae/models/vae.py","file_url":"https://github.com/shi-yu-wang/CorrVAE/blob/HEAD/disvae/models/vae.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c48a1f23f5a0b852"}},{"code_sha256_prefix":"f7f9dc1e55312ed9","entry":"get_activation_name","repo":"karolrogozinski/cern_alice_fast_sim_corrvae","repo_kind":"listed","path":"src/model.py","file_url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae/blob/HEAD/src/model.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f7f9dc1e55312ed9"}},{"code_sha256_prefix":"4dc7cb3426dd30fa","entry":"get_activation_name","repo":"shi-yu-wang/CorrVAE","repo_kind":"found_in_text","path":"disvae/models/vae.py","file_url":"https://github.com/shi-yu-wang/CorrVAE/blob/HEAD/disvae/models/vae.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"4dc7cb3426dd30fa"}},{"code_sha256_prefix":"9881f21a9f54584f","entry":"get_gain","repo":"karolrogozinski/cern_alice_fast_sim_corrvae","repo_kind":"listed","path":"src/model.py","file_url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae/blob/HEAD/src/model.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"9881f21a9f54584f"}},{"code_sha256_prefix":"5c4cf3ccd637667f","entry":"linear_init","repo":"karolrogozinski/cern_alice_fast_sim_corrvae","repo_kind":"listed","path":"src/model.py","file_url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae/blob/HEAD/src/model.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5c4cf3ccd637667f"}},{"code_sha256_prefix":"26c1acd27b4a920f","entry":"linear_init","repo":"shi-yu-wang/CorrVAE","repo_kind":"found_in_text","path":"disvae/models/vae.py","file_url":"https://github.com/shi-yu-wang/CorrVAE/blob/HEAD/disvae/models/vae.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"26c1acd27b4a920f"}},{"code_sha256_prefix":"088e3274539b1ced","entry":"get_gain","repo":"shi-yu-wang/CorrVAE","repo_kind":"found_in_text","path":"disvae/models/vae.py","file_url":"https://github.com/shi-yu-wang/CorrVAE/blob/HEAD/disvae/models/vae.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"088e3274539b1ced"}},{"code_sha256_prefix":"2b53bbe1b1d0c395","entry":"weights_init","repo":"karolrogozinski/cern_alice_fast_sim_corrvae","repo_kind":"listed","path":"src/model.py","file_url":"https://github.com/karolrogozinski/cern_alice_fast_sim_corrvae/blob/HEAD/src/model.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"2b53bbe1b1d0c395"}},{"code_sha256_prefix":"db93b50085c8a8b2","entry":"weights_init","repo":"shi-yu-wang/CorrVAE","repo_kind":"found_in_text","path":"disvae/models/vae.py","file_url":"https://github.com/shi-yu-wang/CorrVAE/blob/HEAD/disvae/models/vae.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"db93b50085c8a8b2"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}