{"id":"https://openalex.org/W3090313932","doi":"https://doi.org/10.1088/2632-2153/ac8393","title":"RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior","display_name":"RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior","publication_year":2022,"publication_date":"2022-07-22","ids":{"openalex":"https://openalex.org/W3090313932","doi":"https://doi.org/10.1088/2632-2153/ac8393","mag":"3090313932"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/ac8393","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ac8393","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ac8393/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ac8393/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070474717","display_name":"Hong-Ye Hu","orcid":"https://orcid.org/0000-0001-5841-831X"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hong-Ye Hu","raw_affiliation_strings":["University of California\u2014San Diego"],"raw_orcid":"https://orcid.org/0000-0001-5841-831X","affiliations":[{"raw_affiliation_string":"University of California\u2014San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086176112","display_name":"Dian Wu","orcid":"https://orcid.org/0000-0003-3888-5003"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dian Wu","raw_affiliation_strings":["Peking University"],"raw_orcid":"https://orcid.org/0000-0003-3888-5003","affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015225562","display_name":"Yi\u2010Zhuang You","orcid":"https://orcid.org/0000-0003-4080-5340"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Zhuang You","raw_affiliation_strings":["University of California\u2014San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California\u2014San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032674291","display_name":"Bruno A. Olshausen","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bruno Olshausen","raw_affiliation_strings":["University of California\u2013Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California\u2013Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013970773","display_name":"Yubei Chen","orcid":"https://orcid.org/0000-0002-8930-3512"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yubei Chen","raw_affiliation_strings":["Facebook AI Research#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-8930-3512","affiliations":[{"raw_affiliation_string":"Facebook AI Research#TAB#","institution_ids":["https://openalex.org/I2252078561"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070474717"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":0.3061,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.51861595,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"3","issue":"3","first_page":"035009","last_page":"035009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9610999822616577,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.7217769026756287},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.6473920941352844},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6195699572563171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5771162509918213},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5166125893592834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5076268911361694},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45842471718788147},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.44393986463546753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44197946786880493},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.43794485926628113},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.41939157247543335},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4086270034313202},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35298898816108704},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.11280640959739685},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07935237884521484}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.7217769026756287},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.6473920941352844},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6195699572563171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5771162509918213},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5166125893592834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5076268911361694},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45842471718788147},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.44393986463546753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44197946786880493},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.43794485926628113},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.41939157247543335},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4086270034313202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35298898816108704},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.11280640959739685},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07935237884521484},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1088/2632-2153/ac8393","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ac8393","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ac8393/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2010.00029","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.00029","pdf_url":"https://arxiv.org/pdf/2010.00029","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:infoscience.epfl.ch:295909","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/295909","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WoS","raw_type":"research article"},{"id":"doi:10.48550/arxiv.2010.00029","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.00029","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:3090313932","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"doi:10.1088/2632-2153/ac8393","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ac8393","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ac8393/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4889846574","display_name":null,"funder_award_id":"1718991","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3090313932.pdf","grobid_xml":"https://content.openalex.org/works/W3090313932.grobid-xml"},"referenced_works_count":86,"referenced_works":["https://openalex.org/W648143168","https://openalex.org/W1692860925","https://openalex.org/W1834627138","https://openalex.org/W1877260383","https://openalex.org/W1890000358","https://openalex.org/W1934222401","https://openalex.org/W1959608418","https://openalex.org/W1971017968","https://openalex.org/W1998236996","https://openalex.org/W1999488180","https://openalex.org/W2010625607","https://openalex.org/W2025153762","https://openalex.org/W2068629287","https://openalex.org/W2093774709","https://openalex.org/W2105464873","https://openalex.org/W2123649031","https://openalex.org/W2132694125","https://openalex.org/W2142809461","https://openalex.org/W2145889472","https://openalex.org/W2154579312","https://openalex.org/W2163846795","https://openalex.org/W2163922914","https://openalex.org/W2170653751","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2246296081","https://openalex.org/W2295130376","https://openalex.org/W2319680621","https://openalex.org/W2331128040","https://openalex.org/W2475287302","https://openalex.org/W2511261638","https://openalex.org/W2557969682","https://openalex.org/W2607839392","https://openalex.org/W2614895328","https://openalex.org/W2619533328","https://openalex.org/W2752444456","https://openalex.org/W2753738274","https://openalex.org/W2785331752","https://openalex.org/W2886348436","https://openalex.org/W2892666903","https://openalex.org/W2894015318","https://openalex.org/W2896712926","https://openalex.org/W2903227570","https://openalex.org/W2903538854","https://openalex.org/W2908510526","https://openalex.org/W2911827218","https://openalex.org/W2920442506","https://openalex.org/W2922301641","https://openalex.org/W2962695743","https://openalex.org/W2962719787","https://openalex.org/W2962750131","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2962808998","https://openalex.org/W2962834855","https://openalex.org/W2963104724","https://openalex.org/W2963139417","https://openalex.org/W2963226019","https://openalex.org/W2963265008","https://openalex.org/W2963317801","https://openalex.org/W2963540976","https://openalex.org/W2963639656","https://openalex.org/W2963685250","https://openalex.org/W2963755523","https://openalex.org/W2964020555","https://openalex.org/W2964127395","https://openalex.org/W2964193438","https://openalex.org/W2970641149","https://openalex.org/W2970700221","https://openalex.org/W2970898247","https://openalex.org/W2979463038","https://openalex.org/W2991563701","https://openalex.org/W2995627237","https://openalex.org/W3004753434","https://openalex.org/W3015134397","https://openalex.org/W3022477152","https://openalex.org/W3029025308","https://openalex.org/W3035574324","https://openalex.org/W3035983404","https://openalex.org/W3041956526","https://openalex.org/W3102159564","https://openalex.org/W3104057828","https://openalex.org/W3104525895","https://openalex.org/W3105369529","https://openalex.org/W3105432754","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2753545915","https://openalex.org/W3037648364","https://openalex.org/W2560998940","https://openalex.org/W2803439868","https://openalex.org/W2756015143","https://openalex.org/W3098527778","https://openalex.org/W2945409826","https://openalex.org/W2083227311","https://openalex.org/W2807371563","https://openalex.org/W2994893577","https://openalex.org/W2133037795","https://openalex.org/W3036206162","https://openalex.org/W3025769139","https://openalex.org/W2963477275","https://openalex.org/W2124369603","https://openalex.org/W1981634377","https://openalex.org/W3173538149","https://openalex.org/W2433138581","https://openalex.org/W2976768568","https://openalex.org/W2965742591"],"abstract_inverted_index":{"Abstract":[0],"Flow-based":[1],"generative":[2,34,169],"models":[3,94,170],"have":[4],"become":[5],"an":[6,159],"important":[7],"class":[8],"of":[9,21,44,77,101,107,132,158],"unsupervised":[10],"learning":[11],"approaches.":[12],"In":[13,111],"this":[14],"work,":[15],"we":[16,88,113],"incorporate":[17],"the":[18,63,68,78,85,98,115,123,130],"key":[19],"ideas":[20],"renormalization":[22],"group":[23],"(RG)":[24],"and":[25,46,62,74,95],"sparse":[26,124],"prior":[27,120],"distribution":[28,121,126],"to":[29,105,127,167],"design":[30],"a":[31,135],"hierarchical":[32],"flow-based":[33,93],"model,":[35],"RG-Flow,":[36],"which":[37],"can":[38],"separate":[39],"information":[40],"at":[41,50,80],"different":[42,81],"scales":[43],"images":[45,79],"extract":[47],"disentangled":[48,69],"representations":[49,70],"each":[51],"scale.":[52],"We":[53],"demonstrate":[54],"our":[55,138],"method":[56,140],"on":[57],"synthetic":[58],"multi-scale":[59],"image":[60,160],"datasets":[61],"CelebA":[64],"dataset,":[65],"showing":[66],"that":[67,97],"enable":[71],"semantic":[72],"manipulation":[73],"style":[75],"mixing":[76],"scales.":[82],"To":[83],"visualize":[84],"latent":[86],"representations,":[87],"introduce":[89],"receptive":[90,99],"fields":[91,100],"for":[92,156],"show":[96],"RG-Flow":[102],"are":[103],"similar":[104],"those":[106],"convolutional":[108],"neural":[109],"networks.":[110],"addition,":[112],"replace":[114],"widely":[116],"adopted":[117],"isotropic":[118],"Gaussian":[119],"by":[122],"Laplacian":[125],"further":[128],"enhance":[129],"disentanglement":[131],"representations.":[133],"From":[134],"theoretical":[136],"perspective,":[137],"proposed":[139],"has":[141],"<mml:math":[142,172],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[143,173],"overflow=\"scroll\">":[144,174],"<mml:mrow>":[145],"<mml:mi>O</mml:mi>":[146,175],"<mml:mo":[147,151,176,182],"stretchy=\"false\">(</mml:mo>":[148,177],"<mml:mi>log</mml:mi>":[149],"<mml:mi>L</mml:mi>":[150,179],"stretchy=\"false\">)</mml:mo>":[152,183],"</mml:mrow>":[153],"</mml:math>":[154,184],"complexity":[155],"inpainting":[157],"with":[161,171],"edge":[162],"length":[163],"L":[164],",":[165],"compared":[166],"previous":[168],"<mml:msup>":[178],"<mml:mn>2</mml:mn>":[180],"</mml:msup>":[181],"complexity.":[185]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
