{"id":"https://openalex.org/W2594169167","doi":"https://doi.org/10.1109/tnnls.2018.2852738","title":"Denoising Adversarial Autoencoders","display_name":"Denoising Adversarial Autoencoders","publication_year":2018,"publication_date":"2018-08-16","ids":{"openalex":"https://openalex.org/W2594169167","doi":"https://doi.org/10.1109/tnnls.2018.2852738","mag":"2594169167","pmid":"https://pubmed.ncbi.nlm.nih.gov/30130236"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2018.2852738","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2852738","pdf_url":"https://ieeexplore.ieee.org/ielx7/5962385/8668600/08438540.pdf","source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/5962385/8668600/08438540.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009239144","display_name":"Antonia Creswell","orcid":"https://orcid.org/0000-0003-1037-9395"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Antonia Creswell","raw_affiliation_strings":["Biologically Inspired Computer Vision Group, Imperial College London, London, U.K","[Biologically Inspired Computer Vision Group, Imperial College London, London, U.K.]"],"affiliations":[{"raw_affiliation_string":"Biologically Inspired Computer Vision Group, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"[Biologically Inspired Computer Vision Group, Imperial College London, London, U.K.]","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027222571","display_name":"Anil A. Bharath","orcid":"https://orcid.org/0000-0001-8808-2714"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Anil Anthony Bharath","raw_affiliation_strings":["Biologically Inspired Computer Vision Group, Imperial College London, London, U.K","[Biologically Inspired Computer Vision Group, Imperial College London, London, U.K.]"],"affiliations":[{"raw_affiliation_string":"Biologically Inspired Computer Vision Group, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"[Biologically Inspired Computer Vision Group, Imperial College London, London, U.K.]","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009239144"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.2125,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52778819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"30","issue":"4","first_page":"968","last_page":"984"},"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":0.9940000176429749,"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":0.9940000176429749,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9840999841690063,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9812999963760376,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.725027322769165},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7115551829338074},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6681862473487854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6393847465515137},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5838465094566345},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5572552680969238},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5472325086593628},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5430895090103149},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5215458869934082},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4326993227005005},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43136733770370483},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2707091271877289}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.725027322769165},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7115551829338074},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6681862473487854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6393847465515137},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5838465094566345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5572552680969238},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5472325086593628},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5430895090103149},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5215458869934082},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4326993227005005},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43136733770370483},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2707091271877289},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/tnnls.2018.2852738","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2852738","pdf_url":"https://ieeexplore.ieee.org/ielx7/5962385/8668600/08438540.pdf","source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:30130236","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30130236","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:1703.01220","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1703.01220","pdf_url":"https://arxiv.org/pdf/1703.01220","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":null},{"id":"mag:2594169167","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1703.01220","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":"pmh:oai:spiral.imperial.ac.uk:10044/1/61801","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/61801","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"984","raw_type":"Journal Article"},{"id":"doi:10.48550/arxiv.1703.01220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1703.01220","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:10.1109/tnnls.2018.2852738","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2852738","pdf_url":"https://ieeexplore.ieee.org/ielx7/5962385/8668600/08438540.pdf","source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.800000011920929,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1830771774","display_name":null,"funder_award_id":"Doctoral Training Studentship","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1934935867","display_name":null,"funder_award_id":"Engineering and Physical Sciences R","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8832984734","display_name":"DTA - Imperial College London","funder_award_id":"EP/L504786/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2594169167.pdf","grobid_xml":"https://content.openalex.org/works/W2594169167.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W2025768430","https://openalex.org/W2100495367","https://openalex.org/W2156163116","https://openalex.org/W2194321275","https://openalex.org/W4231109964","https://openalex.org/W6631190155","https://openalex.org/W6638484148","https://openalex.org/W6639118175","https://openalex.org/W6640963894","https://openalex.org/W6674887261","https://openalex.org/W6679061810","https://openalex.org/W6680067488","https://openalex.org/W6681096077","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6685674053","https://openalex.org/W6686131816","https://openalex.org/W6717697761","https://openalex.org/W6744336401","https://openalex.org/W6744627333","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W2025768430","https://openalex.org/W3123976468","https://openalex.org/W3005116366","https://openalex.org/W2947054491","https://openalex.org/W2884980254","https://openalex.org/W2885367966","https://openalex.org/W2965581080","https://openalex.org/W3002254693","https://openalex.org/W2998764808","https://openalex.org/W2951903140","https://openalex.org/W3133676303","https://openalex.org/W2851950156","https://openalex.org/W2806319940","https://openalex.org/W2962768052","https://openalex.org/W2998453661","https://openalex.org/W3034823697","https://openalex.org/W2914383137","https://openalex.org/W3088887718","https://openalex.org/W3181622257","https://openalex.org/W2135306627"],"abstract_inverted_index":{"Unsupervised":[0],"learning":[1,34,138],"is":[2],"of":[3,15,27,79,101,124,139],"growing":[4],"interest":[5],"because":[6],"it":[7,55],"unlocks":[8],"the":[9,77,80,84,99,120,131,137,169],"potential":[10],"held":[11],"in":[12,83],"vast":[13],"amounts":[14],"unlabeled":[16,37],"data":[17,39,82,171],"to":[18,35,57,75,129,136],"learn":[19],"useful":[20],"representations":[21,47,140],"for":[22,141],"inference.":[23],"Autoencoders,":[24],"a":[25,41,109,153,176],"form":[26],"generative":[28],"model,":[29],"may":[30,48,66,116],"be":[31,49,67,117],"trained":[32,151,174],"by":[33,51,70],"reconstruct":[36],"input":[38,60,170],"from":[40,62],"latent":[42,85,102],"representation":[43],"space.":[44,86],"More":[45],"robust":[46],"produced":[50],"an":[52],"autoencoder":[53],"if":[54],"learns":[56],"recover":[58],"clean":[59],"samples":[61,163],"corrupted":[63],"ones.":[64],"Representations":[65],"further":[68],"improved":[69],"introducing":[71],"regularization":[72],"during":[73],"training":[74,121],"shape":[76],"distribution":[78,100],"encoded":[81],"We":[87,107],"suggest":[88,148],"denoising":[89,95,115,134,154],"adversarial":[90,105],"autoencoders":[91,150],"(AAEs),":[92],"which":[93],"combine":[94],"and":[96,122,143,160],"regularization,":[97],"shaping":[98],"space":[103],"using":[104,152],"training.":[106],"introduce":[108],"novel":[110],"analysis":[111],"that":[112,133,149,164],"shows":[113],"how":[114],"incorporated":[118],"into":[119],"sampling":[123],"AAEs.":[125],"Experiments":[126],"are":[127,165],"performed":[128],"assess":[130],"contributions":[132],"makes":[135],"classification":[142,158],"sample":[144],"synthesis.":[145],"Our":[146],"results":[147],"criterion":[155],"achieve":[156],"higher":[157],"performance":[159],"can":[161],"synthesize":[162],"more":[166],"consistent":[167],"with":[168],"than":[172],"those":[173],"without":[175],"corruption":[177],"process.":[178]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
