{"id":"https://openalex.org/W2915993811","doi":"https://doi.org/10.1145/3293353.3293422","title":"Geometry of Deep Generative Models for Disentangled Representations","display_name":"Geometry of Deep Generative Models for Disentangled Representations","publication_year":2018,"publication_date":"2018-12-18","ids":{"openalex":"https://openalex.org/W2915993811","doi":"https://doi.org/10.1145/3293353.3293422","mag":"2915993811"},"language":"en","primary_location":{"id":"doi:10.1145/3293353.3293422","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3293353.3293422","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3293353.3293422?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3293353.3293422?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023797933","display_name":"Ankita Shukla","orcid":"https://orcid.org/0000-0002-1878-2667"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]},{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ankita Shukla","raw_affiliation_strings":["IIIT-Delhi, Delhi, India","IIIT Delhi  Delhi India"],"affiliations":[{"raw_affiliation_string":"IIIT-Delhi, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]},{"raw_affiliation_string":"IIIT Delhi  Delhi India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045000053","display_name":"Shagun Uppal","orcid":"https://orcid.org/0000-0002-4502-4650"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shagun Uppal","raw_affiliation_strings":["IIIT-Delhi, Delhi, India","IIIT Delhi  Delhi India"],"affiliations":[{"raw_affiliation_string":"IIIT-Delhi, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]},{"raw_affiliation_string":"IIIT Delhi  Delhi India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079864567","display_name":"Sarthak Bhagat","orcid":"https://orcid.org/0000-0002-9067-0926"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sarthak Bhagat","raw_affiliation_strings":["IIIT-Delhi, Delhi, India","IIIT Delhi  Delhi India"],"affiliations":[{"raw_affiliation_string":"IIIT-Delhi, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]},{"raw_affiliation_string":"IIIT Delhi  Delhi India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101551646","display_name":"Saket Anand","orcid":"https://orcid.org/0000-0002-6229-3940"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]},{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saket Anand","raw_affiliation_strings":["IIIT-Delhi, Delhi, India","IIIT Delhi  Delhi India"],"affiliations":[{"raw_affiliation_string":"IIIT-Delhi, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]},{"raw_affiliation_string":"IIIT Delhi  Delhi India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062945520","display_name":"Pavan Turaga","orcid":"https://orcid.org/0000-0002-5263-5943"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pavan Turaga","raw_affiliation_strings":["Arizona State University, Tempe, Arizona, USA","Arizona State University , Tempe, Arizona, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, Arizona, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University , Tempe, Arizona, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5023797933"],"corresponding_institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.14438254,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49110502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9991999864578247,"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":0.9991999864578247,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9739999771118164,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9158999919891357,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.842671275138855},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.5804159045219421},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5704140663146973},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.539426326751709},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5193380117416382},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4764421582221985},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4640597105026245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4635877311229706},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.461668998003006},{"id":"https://openalex.org/keywords/function-space","display_name":"Function space","score":0.4584616422653198},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4155437648296356},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4127811789512634},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3791514039039612},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3583478331565857},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34732478857040405},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.3093993663787842},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.15838095545768738}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.842671275138855},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.5804159045219421},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5704140663146973},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.539426326751709},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5193380117416382},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4764421582221985},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4640597105026245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4635877311229706},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.461668998003006},{"id":"https://openalex.org/C142730499","wikidata":"https://www.wikidata.org/wiki/Q934367","display_name":"Function space","level":2,"score":0.4584616422653198},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4155437648296356},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4127811789512634},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3791514039039612},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3583478331565857},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34732478857040405},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.3093993663787842},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.15838095545768738},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3293353.3293422","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3293353.3293422","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3293353.3293422?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1902.06964","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.06964","pdf_url":"https://arxiv.org/pdf/1902.06964","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":"","raw_type":"text"},{"id":"mag:2915993811","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1902.06964","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1902.06964","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1902.06964","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1145/3293353.3293422","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3293353.3293422","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3293353.3293422?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2915993811.pdf","grobid_xml":"https://content.openalex.org/works/W2915993811.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2966661","https://openalex.org/W1850742715","https://openalex.org/W1915328033","https://openalex.org/W2011582941","https://openalex.org/W2099471712","https://openalex.org/W2123921160","https://openalex.org/W2157617585","https://openalex.org/W2158097970","https://openalex.org/W2173520492","https://openalex.org/W2188956040","https://openalex.org/W2194775991","https://openalex.org/W2342792901","https://openalex.org/W2767614780","https://openalex.org/W2804013387","https://openalex.org/W2909751683","https://openalex.org/W2951004968","https://openalex.org/W2951392118","https://openalex.org/W2951751411","https://openalex.org/W2952225049","https://openalex.org/W2964231450"],"related_works":["https://openalex.org/W3021886971","https://openalex.org/W3100891210","https://openalex.org/W3126812234","https://openalex.org/W2993459822","https://openalex.org/W2887374224","https://openalex.org/W3109940000","https://openalex.org/W2962936818","https://openalex.org/W1869311973","https://openalex.org/W2910986402","https://openalex.org/W2307349589","https://openalex.org/W2962796133","https://openalex.org/W2137348666","https://openalex.org/W2953704784","https://openalex.org/W2158418925","https://openalex.org/W1502853028","https://openalex.org/W2227319605","https://openalex.org/W3206956093","https://openalex.org/W1859141211","https://openalex.org/W3087071970","https://openalex.org/W3104821590"],"abstract_inverted_index":{"Deep":[0],"generative":[1,53,84],"models":[2,54,85,104,148],"like":[3],"variational":[4,137,150],"autoencoders":[5],"approximate":[6],"the":[7,35,43,46,80,96,113,121,126,143,165,176,179],"intrinsic":[8],"geometry":[9,81,144],"of":[10,27,37,42,45,82,98,101,107,112,145,178],"high":[11],"dimensional":[12],"data":[13],"manifolds":[14],"by":[15],"learning":[16,59],"low-dimensional":[17],"latent-space":[18],"variables":[19],"and":[20,110,141,162],"an":[21],"embedding":[22],"function.":[23,48],"The":[24,115],"geometric":[25],"properties":[26,97],"these":[28,183],"latent":[29,99,128,166],"spaces":[30,100],"has":[31],"been":[32,56],"studied":[33],"under":[34],"lens":[36],"Riemannian":[38,172],"geometry;":[39],"via":[40],"analysis":[41],"non-linearity":[44],"generator":[47],"In":[49,75],"new":[50],"developments,":[51],"deep":[52],"have":[55,186],"used":[57],"for":[58,86],"semantically":[60],"meaningful":[61],"`disentangled'":[62],"representations;":[63],"that":[64,120,160],"capture":[65],"task":[66],"relevant":[67],"attributes":[68],"while":[69],"being":[70],"invariant":[71],"to":[72,94,135],"other":[73],"attributes.":[74],"this":[76],"work,":[77],"we":[78,117],"explore":[79],"popular":[83],"disentangled":[87,102,127],"representation":[88,103],"learning.":[89],"We":[90,139,181],"use":[91],"several":[92],"metrics":[93,173],"compare":[95,142],"in":[105,125,164],"terms":[106],"class":[108,122],"separability":[109],"curvature":[111,132,177],"latent-space.":[114],"results":[116,158,184],"obtain":[118],"establish":[119],"distinguishable":[123],"features":[124],"space":[129,167],"exhibits":[130],"higher":[131],"as":[133,198,200],"opposed":[134],"a":[136],"autoencoder.":[138],"evaluate":[140],"three":[146],"such":[147],"with":[149,171],"autoencoder":[151],"on":[152,188],"two":[153],"different":[154],"datasets.":[155],"Further,":[156],"our":[157],"show":[159],"distances":[161],"interpolation":[163],"are":[168],"significantly":[169],"improved":[170],"derived":[174],"from":[175],"space.":[180],"expect":[182],"will":[185],"implications":[187],"understanding":[189],"how":[190],"deep-networks":[191],"can":[192],"be":[193],"made":[194],"more":[195],"robust,":[196],"generalizable,":[197],"well":[199],"interpretable.":[201]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}