{"id":"https://openalex.org/W3150406472","doi":"https://doi.org/10.1162/neco_a_01434","title":"Parametric UMAP Embeddings for Representation and Semisupervised Learning","display_name":"Parametric UMAP Embeddings for Representation and Semisupervised Learning","publication_year":2021,"publication_date":"2021-08-30","ids":{"openalex":"https://openalex.org/W3150406472","doi":"https://doi.org/10.1162/neco_a_01434","mag":"3150406472","pmid":"https://pubmed.ncbi.nlm.nih.gov/34474477"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_01434","is_oa":true,"landing_page_url":"https://doi.org/10.1162/neco_a_01434","pdf_url":"https://direct.mit.edu/neco/article-pdf/33/11/2881/1966656/neco_a_01434.pdf","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":"preprint","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://direct.mit.edu/neco/article-pdf/33/11/2881/1966656/neco_a_01434.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021871239","display_name":"Tim Sainburg","orcid":"https://orcid.org/0000-0003-4223-2689"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tim Sainburg","raw_affiliation_strings":["University of California San Diego, La Jolla, CA 92093, U.S.A. timsainb@gmail.com"],"affiliations":[{"raw_affiliation_string":"University of California San Diego, La Jolla, CA 92093, U.S.A. timsainb@gmail.com","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072564294","display_name":"Leland McInnes","orcid":"https://orcid.org/0000-0003-2143-6834"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leland McInnes","raw_affiliation_strings":["Tutte Institute for Mathematics and Computing, Ottawa, Ontario Canada leland.mcinnes@gmail.com"],"affiliations":[{"raw_affiliation_string":"Tutte Institute for Mathematics and Computing, Ottawa, Ontario Canada leland.mcinnes@gmail.com","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035993162","display_name":"Timothy Q. Gentner","orcid":"https://orcid.org/0000-0002-4516-9841"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy Q. Gentner","raw_affiliation_strings":["University of California San Diego, La Jolla, CA 92093, U.S.A. tgentner@ucsd.edu"],"affiliations":[{"raw_affiliation_string":"University of California San Diego, La Jolla, CA 92093, U.S.A. tgentner@ucsd.edu","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021871239"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":4.827,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.95476965,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"33","issue":"11","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9937999844551086,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.7167319655418396},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6086610555648804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6081964373588562},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6030979752540588},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5587603449821472},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.47877347469329834},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47694721817970276},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46413347125053406},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4617064297199249},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3765716552734375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.28638848662376404},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2846253514289856}],"concepts":[{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.7167319655418396},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6086610555648804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6081964373588562},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6030979752540588},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5587603449821472},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.47877347469329834},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47694721817970276},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46413347125053406},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4617064297199249},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3765716552734375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28638848662376404},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2846253514289856},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1162/neco_a_01434","is_oa":true,"landing_page_url":"https://doi.org/10.1162/neco_a_01434","pdf_url":"https://direct.mit.edu/neco/article-pdf/33/11/2881/1966656/neco_a_01434.pdf","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:34474477","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34474477","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:arXiv.org:2009.12981","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.12981","pdf_url":"https://arxiv.org/pdf/2009.12981","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":null,"raw_type":"text"},{"id":"mag:3150406472","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2009.12981.pdf","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:escholarship.org:ark:/13030/qt6dc0b8c0","is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/6dc0b8c0","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Neural Computation, vol 33, iss 11","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8516496","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8516496","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Neural Comput","raw_type":"Text"},{"id":"doi:10.48550/arxiv.2009.12981","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2009.12981","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:10.1162/neco_a_01434","is_oa":true,"landing_page_url":"https://doi.org/10.1162/neco_a_01434","pdf_url":"https://direct.mit.edu/neco/article-pdf/33/11/2881/1966656/neco_a_01434.pdf","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3150406472.pdf","grobid_xml":"https://content.openalex.org/works/W3150406472.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W175240224","https://openalex.org/W659060387","https://openalex.org/W1875842236","https://openalex.org/W1959608418","https://openalex.org/W1987971958","https://openalex.org/W1997780235","https://openalex.org/W2020984122","https://openalex.org/W2043508111","https://openalex.org/W2057491655","https://openalex.org/W2110026675","https://openalex.org/W2116516955","https://openalex.org/W2156287497","https://openalex.org/W2187089797","https://openalex.org/W2294044338","https://openalex.org/W2318862053","https://openalex.org/W2567627528","https://openalex.org/W2750384547","https://openalex.org/W2777699329","https://openalex.org/W2786672974","https://openalex.org/W2797173239","https://openalex.org/W2883961755","https://openalex.org/W2901716970","https://openalex.org/W2902652978","https://openalex.org/W2945817187","https://openalex.org/W2949272108","https://openalex.org/W2951777958","https://openalex.org/W2968378480","https://openalex.org/W2996501936","https://openalex.org/W3001197829","https://openalex.org/W3034266300","https://openalex.org/W3042544668","https://openalex.org/W3100300767","https://openalex.org/W3105146463","https://openalex.org/W3118608800","https://openalex.org/W3127452014"],"related_works":["https://openalex.org/W3088566120","https://openalex.org/W3197209004","https://openalex.org/W3197783987","https://openalex.org/W3144740033","https://openalex.org/W4205823344","https://openalex.org/W2948868064","https://openalex.org/W2156663121","https://openalex.org/W3120749165","https://openalex.org/W2921038341","https://openalex.org/W2177424816","https://openalex.org/W1563289859","https://openalex.org/W2131187138","https://openalex.org/W2766664464","https://openalex.org/W2042453128","https://openalex.org/W3105250825","https://openalex.org/W154035730","https://openalex.org/W2766197118","https://openalex.org/W2330699524","https://openalex.org/W3033649369","https://openalex.org/W3042544668"],"abstract_inverted_index":{"UMAP":[0,23,61,83,109],"is":[1],"a":[2,31,35,48,63,71,95,111],"nonparametric":[3,88],"graph-based":[4],"dimensionality":[5],"reduction":[6],"algorithm":[7,24],"using":[8],"applied":[9],"Riemannian":[10],"geometry":[11],"and":[12,41,76,124],"algebraic":[13],"topology":[14],"to":[15,62,86],"find":[16],"low-dimensional":[17,49],"embeddings":[18,102],"of":[19,26,34,51,60,94,117],"structured":[20],"data.":[21],"The":[22],"consists":[25],"two":[27],"steps:":[28],"(1)":[29],"computing":[30],"graphical":[32],"representation":[33],"data":[36,75],"set":[37],"(fuzzy":[38],"simplicial":[39],"complex)":[40],"(2)":[42],"through":[43],"stochastic":[44],"gradient":[45],"descent,":[46],"optimizing":[47],"embedding":[50],"the":[52,57,92,114],"graph.":[53],"Here,":[54],"we":[55],"extend":[56],"second":[58],"step":[59],"parametric":[64,72,82,97],"optimization":[65],"over":[66],"neural":[67],"network":[68],"weights,":[69],"learning":[70,130],"relationship":[73],"between":[74],"embedding.":[77],"We":[78,106],"first":[79],"demonstrate":[80],"that":[81],"performs":[84],"comparably":[85],"its":[87],"counterpart":[89],"while":[90],"conferring":[91],"benefit":[93],"learned":[96],"mapping":[98],"(e.g.,":[99],"fast":[100],"online":[101],"for":[103,128],"new":[104],"data).":[105],"then":[107],"explore":[108],"as":[110],"regularization,":[112],"constraining":[113],"latent":[115],"distribution":[116],"autoencoders,":[118],"parametrically":[119],"varying":[120],"global":[121],"structure":[122,133],"preservation,":[123],"improving":[125],"classifier":[126],"accuracy":[127],"semisupervised":[129],"by":[131],"capturing":[132],"in":[134],"unlabeled":[135],"data.1.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
