{"id":"https://openalex.org/W2013035813","doi":"https://doi.org/10.1162/neco_a_00142","title":"A Connection Between Score Matching and Denoising Autoencoders","display_name":"A Connection Between Score Matching and Denoising Autoencoders","publication_year":2011,"publication_date":"2011-04-15","ids":{"openalex":"https://openalex.org/W2013035813","doi":"https://doi.org/10.1162/neco_a_00142","mag":"2013035813","pmid":"https://pubmed.ncbi.nlm.nih.gov/21492012"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_00142","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_00142","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5103958886","display_name":"Pascal Vincent","orcid":null},"institutions":[{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Pascal Vincent","raw_affiliation_strings":["D\u00e9partement d\u2019Informatique, Universit\u00e9 de Montr\u00e9al, Montr\u00e9al (QC) H3C 3J7, Canada"],"affiliations":[{"raw_affiliation_string":"D\u00e9partement d\u2019Informatique, Universit\u00e9 de Montr\u00e9al, Montr\u00e9al (QC) H3C 3J7, Canada","institution_ids":["https://openalex.org/I70931966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103958886"],"corresponding_institution_ids":["https://openalex.org/I70931966"],"apc_list":null,"apc_paid":null,"fwci":10.7248,"has_fulltext":false,"cited_by_count":942,"citation_normalized_percentile":{"value":0.98725773,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"23","issue":"7","first_page":"1661","last_page":"1674"},"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":0.8543999791145325,"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":0.8543999791145325,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.029999999329447746,"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/T11751","display_name":"Lattice Boltzmann Simulation Studies","score":0.022700000554323196,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8284410238265991},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.7704977989196777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6579650044441223},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6560884714126587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5655731558799744},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5265289545059204},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5057730674743652},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.48775678873062134},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.46963736414909363},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.44036680459976196},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.4403289556503296},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4193817973136902},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4107429087162018},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37629204988479614},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3597673773765564},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34830325841903687},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15405309200286865}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8284410238265991},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.7704977989196777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6579650044441223},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6560884714126587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5655731558799744},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5265289545059204},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5057730674743652},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.48775678873062134},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.46963736414909363},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.44036680459976196},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.4403289556503296},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4193817973136902},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4107429087162018},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37629204988479614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3597673773765564},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34830325841903687},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15405309200286865},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1162/neco_a_00142","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_00142","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},{"id":"pmid:21492012","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21492012","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":"Neural computation","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.190.6457","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.6457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.iro.umontreal.ca/%7Evincentp/Publications/smdae_techreport_1358.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1505878979","https://openalex.org/W1603152151","https://openalex.org/W1981276685","https://openalex.org/W2025768430","https://openalex.org/W2051144468","https://openalex.org/W2059448777","https://openalex.org/W2110798204","https://openalex.org/W2113300847","https://openalex.org/W2116064496","https://openalex.org/W2123496278","https://openalex.org/W2124601597","https://openalex.org/W2124914669","https://openalex.org/W2136922672","https://openalex.org/W2138857742","https://openalex.org/W2140622310","https://openalex.org/W2145094598","https://openalex.org/W2156047073","https://openalex.org/W2161672593","https://openalex.org/W2163922914","https://openalex.org/W2166027445","https://openalex.org/W2171282218","https://openalex.org/W2183660452","https://openalex.org/W2591957553","https://openalex.org/W2595002104","https://openalex.org/W2595697910","https://openalex.org/W2596585349","https://openalex.org/W2606321545","https://openalex.org/W2609208295","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3088732000","https://openalex.org/W2145836866","https://openalex.org/W3037110488","https://openalex.org/W2806873178","https://openalex.org/W2965146396","https://openalex.org/W2770818364","https://openalex.org/W4367312605","https://openalex.org/W4404095322","https://openalex.org/W4312416532"],"abstract_inverted_index":{"Denoising":[0],"autoencoders":[1,136],"have":[2],"been":[3],"previously":[4],"shown":[5],"to":[6,10,35,41,49,82,97,104,106,130,137],"be":[7],"competitive":[8],"alternatives":[9],"restricted":[11],"Boltzmann":[12],"machines":[13],"for":[14,71],"unsupervised":[15],"pretraining":[16],"of":[17,20,44,51,57,119,134,141],"each":[18],"layer":[19],"a":[21,27,45,52,67,94,138],"deep":[22],"architecture.":[23],"We":[24],"show":[25],"that":[26,50,101],"simple":[28],"denoising":[29,73,135],"autoencoder":[30,74],"training":[31],"criterion":[32],"is":[33,102],"equivalent":[34],"matching":[36,100],"the":[37,42,58,72,117,123,132],"score":[38,99],"(with":[39],"respect":[40],"data)":[43],"specific":[46],"energy-based":[47,142],"model":[48,70],"nonparametric":[53],"Parzen":[54],"density":[55],"estimator":[56],"data.":[59],"This":[60],"yields":[61],"several":[62],"useful":[63],"insights.":[64],"It":[65,92,115],"defines":[66],"proper":[68],"probabilistic":[69],"technique,":[75],"which":[76],"makes":[77],"it":[78],"in":[79],"principle":[80],"possible":[81],"sample":[83],"from":[84],"them":[85],"or":[86],"rank":[87],"examples":[88],"by":[89],"their":[90],"energy.":[91],"suggests":[93,128],"different":[95],"way":[96],"apply":[98],"related":[103],"learning":[105],"denoise":[107],"and":[108,125,127],"does":[109],"not":[110],"require":[111],"computing":[112],"second":[113],"derivatives.":[114],"justifies":[116],"use":[118],"tied":[120],"weights":[121],"between":[122],"encoder":[124],"decoder":[126],"ways":[129],"extend":[131],"success":[133],"larger":[139],"family":[140],"models.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":30},{"year":2025,"cited_by_count":244},{"year":2024,"cited_by_count":202},{"year":2023,"cited_by_count":132},{"year":2022,"cited_by_count":52},{"year":2021,"cited_by_count":66},{"year":2020,"cited_by_count":62},{"year":2019,"cited_by_count":31},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":23},{"year":2016,"cited_by_count":22},{"year":2015,"cited_by_count":15},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":14},{"year":2012,"cited_by_count":9}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}