{"id":"https://openalex.org/W3013926797","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048921","title":"A Closer Look at Disentangling in \u03b2-VAE","display_name":"A Closer Look at Disentangling in \u03b2-VAE","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3013926797","doi":"https://doi.org/10.1109/ieeeconf44664.2019.9048921","mag":"3013926797"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf44664.2019.9048921","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052730617","display_name":"Harshvardhan Sikka","orcid":"https://orcid.org/0000-0002-4006-6659"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Harshvardhan Sikka","raw_affiliation_strings":["School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103885739","display_name":"Weishun Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weishun Zhong","raw_affiliation_strings":["Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061151793","display_name":"J. Yin","orcid":"https://orcid.org/0000-0002-2047-206X"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Yin","raw_affiliation_strings":["Department of Physics, Harvard University, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Physics, Harvard University, Cambridge, MA, USA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038508243","display_name":"Cengiz Pehlevant","orcid":null},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cengiz Pehlevant","raw_affiliation_strings":["School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5052730617"],"corresponding_institution_ids":["https://openalex.org/I136199984"],"apc_list":null,"apc_paid":null,"fwci":0.6127,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.73904134,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"888","last_page":"895"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T10320","display_name":"Neural Networks and Applications","score":0.9977999925613403,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9962000250816345,"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/inference","display_name":"Inference","score":0.6917255520820618},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6164558529853821},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5872516632080078},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5629697442054749},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.5533186197280884},{"id":"https://openalex.org/keywords/conditional-independence","display_name":"Conditional independence","score":0.5239253640174866},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5039755702018738},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5030702948570251},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4948827624320984},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.48838895559310913},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.4525845944881439},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4521231949329376},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.44974568486213684},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.43862974643707275},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.43377768993377686},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.37320923805236816},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3305562436580658},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3037911057472229},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.224534809589386},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16453465819358826}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6917255520820618},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6164558529853821},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5872516632080078},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5629697442054749},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.5533186197280884},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.5239253640174866},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5039755702018738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5030702948570251},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4948827624320984},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.48838895559310913},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4525845944881439},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4521231949329376},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.44974568486213684},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.43862974643707275},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.43377768993377686},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.37320923805236816},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3305562436580658},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3037911057472229},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.224534809589386},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16453465819358826},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf44664.2019.9048921","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf44664.2019.9048921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.49000000953674316,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1516111018","https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W1971017968","https://openalex.org/W2102409316","https://openalex.org/W2105464873","https://openalex.org/W2123649031","https://openalex.org/W2125027820","https://openalex.org/W2163922914","https://openalex.org/W2467604901","https://openalex.org/W2585198072","https://openalex.org/W2619034550","https://openalex.org/W2621350877","https://openalex.org/W2621357189","https://openalex.org/W2737047298","https://openalex.org/W2753738274","https://openalex.org/W2766227112","https://openalex.org/W2807692250","https://openalex.org/W2892100238","https://openalex.org/W2902476877","https://openalex.org/W2903538854","https://openalex.org/W2948978827","https://openalex.org/W2950662112","https://openalex.org/W2956607501","https://openalex.org/W2962770929","https://openalex.org/W2963045453","https://openalex.org/W2963264829","https://openalex.org/W2963890275","https://openalex.org/W3103543904","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6675401909","https://openalex.org/W6720208624","https://openalex.org/W6738467200","https://openalex.org/W6738835615","https://openalex.org/W6739139180","https://openalex.org/W6744627333","https://openalex.org/W6745511271","https://openalex.org/W6750298367","https://openalex.org/W6754837808","https://openalex.org/W6756663807","https://openalex.org/W6756824971","https://openalex.org/W6765554853"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2145836866","https://openalex.org/W2734887215","https://openalex.org/W2988134182","https://openalex.org/W2331205114"],"abstract_inverted_index":{"In":[0],"many":[1],"data":[2,24],"analysis":[3],"tasks,":[4],"it":[5],"is":[6,14,75],"beneficial":[7],"to":[8,98],"learn":[9],"representations":[10,32,55],"where":[11],"each":[12],"dimension":[13],"statistically":[15,29],"independent":[16],"and":[17,89],"thus":[18],"disentangled":[19,31],"from":[20],"the":[21,47,81],"others.":[22],"If":[23],"generating":[25],"factors":[26],"are":[27],"also":[28],"independent,":[30],"can":[33],"be":[34],"formed":[35],"by":[36,69],"Bayesian":[37],"inference":[38,101],"of":[39,46,64,84],"latent":[40],"variables.":[41],"We":[42],"examine":[43],"a":[44,99,107],"generalization":[45],"Variational":[48],"Autoencoder":[49],"(VAE),":[50],"\u03b2-VAE,":[51],"for":[52],"learning":[53],"such":[54],"using":[56],"variational":[57],"inference.":[58],"\u03b2":[59,104,110],"-VAE":[60,105],"enforces":[61],"conditional":[62],"independence":[63,83],"its":[65,70],"bottleneck":[66],"neurons":[67],"controlled":[68],"hyperparameter":[71],"\u03b2.":[72],"This":[73],"condition":[74],"in":[76,103],"general":[77],"not":[78],"compatible":[79],"with":[80,106],"statistical":[82],"latents.":[85],"By":[86],"providing":[87],"analytical":[88],"numerical":[90],"arguments,":[91],"we":[92],"show":[93],"that":[94],"this":[95],"incompatibility":[96],"leads":[97],"non-monotonic":[100],"performance":[102],"finite":[108],"optimal":[109],".":[111]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}