{"id":"https://openalex.org/W2511114923","doi":"https://doi.org/10.1109/ijcnn.2017.7965870","title":"Variational methods for conditional multimodal deep learning","display_name":"Variational methods for conditional multimodal deep learning","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2511114923","doi":"https://doi.org/10.1109/ijcnn.2017.7965870","mag":"2511114923"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7965870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7965870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1603.01801","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004812994","display_name":"Gaurav Pandey","orcid":"https://orcid.org/0000-0003-1939-679X"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Gaurav Pandey","raw_affiliation_strings":["Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India","Department of Computer Science and Automation Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Department of Computer Science and Automation Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010292297","display_name":"Ambedkar Dukkipati","orcid":"https://orcid.org/0000-0002-6352-6283"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ambedkar Dukkipati","raw_affiliation_strings":["Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India","Department of Computer Science and Automation Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Department of Computer Science and Automation Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59270414"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"308","last_page":"315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9965999722480774,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9955999851226807,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8164626955986023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.704408586025238},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6401072144508362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6163561940193176},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5978294014930725},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.5970734357833862},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.5966922640800476},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5805780291557312},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5766457915306091},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5230330228805542},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5048640370368958},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.4661845862865448},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.41131383180618286},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3652580976486206},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21367007493972778},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08175826072692871}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8164626955986023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.704408586025238},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6401072144508362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6163561940193176},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5978294014930725},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.5970734357833862},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.5966922640800476},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5805780291557312},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5766457915306091},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5230330228805542},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5048640370368958},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.4661845862865448},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.41131383180618286},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3652580976486206},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21367007493972778},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08175826072692871},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"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/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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/ijcnn.2017.7965870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7965870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.iisc.ac.in:59553","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196309","display_name":"NOT FOUND REPOSITORY (Indian Institute of Science Bangalore)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},{"id":"pmh:oai:arXiv.org:1603.01801","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.01801","pdf_url":"https://arxiv.org/pdf/1603.01801","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:2511114923","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1603.01801v2","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.1603.01801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1603.01801","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1603.01801","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.01801","pdf_url":"https://arxiv.org/pdf/1603.01801","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2511114923.pdf","grobid_xml":"https://content.openalex.org/works/W2511114923.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W189596042","https://openalex.org/W753012316","https://openalex.org/W1553830511","https://openalex.org/W1782590233","https://openalex.org/W1909320841","https://openalex.org/W1959608418","https://openalex.org/W2096175520","https://openalex.org/W2098694378","https://openalex.org/W2099471712","https://openalex.org/W2125389028","https://openalex.org/W2136922672","https://openalex.org/W2138857742","https://openalex.org/W2139427956","https://openalex.org/W2146502635","https://openalex.org/W2148463593","https://openalex.org/W2163614729","https://openalex.org/W2164587673","https://openalex.org/W2184188583","https://openalex.org/W2536626143","https://openalex.org/W2949416428","https://openalex.org/W2951446714","https://openalex.org/W2953267151","https://openalex.org/W6606244218","https://openalex.org/W6607775107","https://openalex.org/W6622239757","https://openalex.org/W6639732818","https://openalex.org/W6640963894","https://openalex.org/W6675944832","https://openalex.org/W6679061810","https://openalex.org/W6681435938","https://openalex.org/W6681753794","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W2963246109","https://openalex.org/W2963801305","https://openalex.org/W3083794923","https://openalex.org/W2914848199","https://openalex.org/W2928100243","https://openalex.org/W3093192273","https://openalex.org/W2803788852","https://openalex.org/W2776110275","https://openalex.org/W2979915069","https://openalex.org/W2011699475","https://openalex.org/W1520325657","https://openalex.org/W2885143803","https://openalex.org/W2925244468","https://openalex.org/W3157517656","https://openalex.org/W2809657535","https://openalex.org/W3012805373","https://openalex.org/W2952411345","https://openalex.org/W3125601066","https://openalex.org/W2977949008","https://openalex.org/W2464714129"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,39,52,78],"address":[4,53],"the":[5,20,54,61,69,87,100,109,120,126,136,158,165,171,177,183],"problem":[6,55],"of":[7,135,182],"conditional":[8,49,58,71,82],"modality":[9,18,94],"learning,":[10],"whereby":[11,157],"one":[12,17],"is":[13,24],"interested":[14],"in":[15,173,186],"generating":[16],"given":[19],"other.":[21],"While":[22],"it":[23],"straightforward":[25],"to":[26,80,96,99,112],"learn":[27],"a":[28,35,92,154],"joint":[29,101],"distribution":[30],"over":[31],"multiple":[32,105],"modalities":[33],"using":[34,125],"deep":[36,75,148],"multi-modal":[37],"architecture,":[38],"observe":[40,169],"that":[41,119,170],"such":[42],"models":[43],"are":[44,129,161,180],"not":[45],"very":[46],"effective":[47],"at":[48],"generation.":[50],"Hence,":[51],"by":[56,146,163,176],"learning":[57],"distributions":[59],"between":[60],"modalities.":[62,106],"We":[63,107,117,151,168],"use":[64,108],"variational":[65],"methods":[66],"for":[67],"maximizing":[68],"corresponding":[70,166,184],"log-likelihood.":[72],"The":[73],"resultant":[74],"model,":[76],"which":[77,139],"refer":[79],"as":[81],"multimodal":[83],"autoencoder":[84],"(CMMA),":[85],"forces":[86],"latent":[88],"representation":[89,102],"obtained":[90,103,145],"from":[91,104,115,123,138],"single":[93],"alone":[95],"be":[97],"`close'":[98],"proposed":[110,127,178],"model":[111,128,179],"generate":[113],"faces":[114,121,160],"attributes.":[116,167,187],"show":[118],"generated":[122],"attributes":[124,137],"qualitatively":[130],"and":[131],"quantitatively":[132],"more":[133],"representative":[134,181],"they":[140],"were":[141],"generated,":[142],"than":[143],"those":[144],"other":[147],"generative":[149],"models.":[150],"also":[152],"propose":[153],"secondary":[155],"task,":[156],"existing":[159],"modified":[162],"modifying":[164],"modifications":[172,185],"face":[174],"introduced":[175]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}