{"id":"https://openalex.org/W3202271651","doi":"https://doi.org/10.1109/tvcg.2021.3114872","title":"A Domain-Oblivious Approach for Learning Concise Representations of Filtered Topological Spaces for Clustering","display_name":"A Domain-Oblivious Approach for Learning Concise Representations of Filtered Topological Spaces for Clustering","publication_year":2021,"publication_date":"2021-09-29","ids":{"openalex":"https://openalex.org/W3202271651","doi":"https://doi.org/10.1109/tvcg.2021.3114872","mag":"3202271651","pmid":"https://pubmed.ncbi.nlm.nih.gov/34587087"},"language":"en","primary_location":{"id":"doi:10.1109/tvcg.2021.3114872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2021.3114872","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","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":null,"display_name":"Yu Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yu Qin","raw_affiliation_strings":["Tulane University, United States"],"affiliations":[{"raw_affiliation_string":"Tulane University, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Brittany Terese Fasy","orcid":null},"institutions":[{"id":"https://openalex.org/I23732399","display_name":"Montana State University","ror":"https://ror.org/02w0trx84","country_code":"US","type":"education","lineage":["https://openalex.org/I23732399","https://openalex.org/I4210126032"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brittany Terese Fasy","raw_affiliation_strings":["Montana State University, United States"],"affiliations":[{"raw_affiliation_string":"Montana State University, United States","institution_ids":["https://openalex.org/I23732399"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Carola Wenk","orcid":null},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carola Wenk","raw_affiliation_strings":["Tulane University, United States"],"affiliations":[{"raw_affiliation_string":"Tulane University, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"last","author":{"id":null,"display_name":"Brian Summa","orcid":null},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Summa","raw_affiliation_strings":["Tulane University, United States"],"affiliations":[{"raw_affiliation_string":"Tulane University, United States","institution_ids":["https://openalex.org/I114832834"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114832834"],"apc_list":null,"apc_paid":null,"fwci":0.6026,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72633017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"28","issue":"1","first_page":"302","last_page":"312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9879000186920166,"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":0.9879000186920166,"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/T10799","display_name":"Data Visualization and Analytics","score":0.006500000134110451,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.00039999998989515007,"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/cluster-analysis","display_name":"Cluster analysis","score":0.6312000155448914},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.5710999965667725},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5339999794960022},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4871000051498413},{"id":"https://openalex.org/keywords/topological-data-analysis","display_name":"Topological data analysis","score":0.3995000123977661},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.39419999718666077},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.3912999927997589},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.3531999886035919},{"id":"https://openalex.org/keywords/diagram","display_name":"Diagram","score":0.3305000066757202}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7734000086784363},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6312000155448914},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.5710999965667725},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5339999794960022},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4871000051498413},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48559999465942383},{"id":"https://openalex.org/C2776477805","wikidata":"https://www.wikidata.org/wiki/Q4460773","display_name":"Topological data analysis","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3912999927997589},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3887999951839447},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C186399060","wikidata":"https://www.wikidata.org/wiki/Q959962","display_name":"Diagram","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3240000009536743},{"id":"https://openalex.org/C2874115","wikidata":"https://www.wikidata.org/wiki/Q17099562","display_name":"Persistent homology","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3190999925136566},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3093000054359436},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.302700012922287},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3021000027656555},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29919999837875366},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.29179999232292175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tvcg.2021.3114872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2021.3114872","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},{"id":"pmid:34587087","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34587087","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 visualization and computer graphics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W124643305","https://openalex.org/W127493627","https://openalex.org/W1600748172","https://openalex.org/W1901057238","https://openalex.org/W1920826835","https://openalex.org/W1960384938","https://openalex.org/W1974647172","https://openalex.org/W1996881001","https://openalex.org/W2004302513","https://openalex.org/W2007052372","https://openalex.org/W2009172320","https://openalex.org/W2027277859","https://openalex.org/W2030644393","https://openalex.org/W2036780368","https://openalex.org/W2037613900","https://openalex.org/W2047158247","https://openalex.org/W2057869046","https://openalex.org/W2074668987","https://openalex.org/W2075608792","https://openalex.org/W2096510084","https://openalex.org/W2096736341","https://openalex.org/W2097117768","https://openalex.org/W2097835496","https://openalex.org/W2104284394","https://openalex.org/W2120683613","https://openalex.org/W2122007052","https://openalex.org/W2122101130","https://openalex.org/W2124511088","https://openalex.org/W2145065594","https://openalex.org/W2157305458","https://openalex.org/W2157514509","https://openalex.org/W2157701289","https://openalex.org/W2171790913","https://openalex.org/W2294510945","https://openalex.org/W2461086877","https://openalex.org/W2509619282","https://openalex.org/W2614596590","https://openalex.org/W2739107216","https://openalex.org/W2789480745","https://openalex.org/W2798956329","https://openalex.org/W2901191984","https://openalex.org/W2912031427","https://openalex.org/W2956257765","https://openalex.org/W2962874918","https://openalex.org/W2963417577","https://openalex.org/W2963470893","https://openalex.org/W2963626527","https://openalex.org/W2976701207","https://openalex.org/W3004917954","https://openalex.org/W3009330671","https://openalex.org/W3138205514","https://openalex.org/W3138447845","https://openalex.org/W3173682628","https://openalex.org/W3211074487","https://openalex.org/W4234143236","https://openalex.org/W4297831948","https://openalex.org/W6675354045","https://openalex.org/W6678556256","https://openalex.org/W6682962330","https://openalex.org/W6684181414","https://openalex.org/W6694154208","https://openalex.org/W6694289516","https://openalex.org/W6695314431","https://openalex.org/W6697214482","https://openalex.org/W6715519383","https://openalex.org/W6739884731","https://openalex.org/W6743496644","https://openalex.org/W6745499037","https://openalex.org/W6748179619","https://openalex.org/W6751417305","https://openalex.org/W6758176539","https://openalex.org/W6761452831","https://openalex.org/W6766964508","https://openalex.org/W6775836593","https://openalex.org/W6787022024","https://openalex.org/W6968564067"],"related_works":[],"abstract_inverted_index":{"Persistence":[0],"diagrams":[1,24,93],"have":[2,98],"been":[3,32],"widely":[4],"used":[5],"to":[6,35,81,132,170,186],"quantify":[7],"the":[8,36,83,136,140,171,179,187,193,224],"underlying":[9],"features":[10],"of":[11,55,63,87,106,173,183,195,226],"filtered":[12],"topological":[13,153],"spaces":[14],"in":[15,101,111],"data":[16],"visualization.":[17],"In":[18,39,189],"many":[19],"applications,":[20],"computing":[21,28],"distances":[22,30],"between":[23,156],"is":[25,67,109,129,206,220],"essential;":[26],"however,":[27],"these":[29],"has":[31],"challenging":[33],"due":[34],"computational":[37],"cost.":[38],"this":[40,107,164],"paper,":[41],"we":[42,91,166,177,191],"propose":[43],"a":[44,51,70,76,124,199],"persistence":[45,56,203],"diagram":[46,77,174],"hashing":[47],"framework":[48,66,169],"that":[49,112,217],"learns":[50],"binary":[52,95,143],"code":[53],"representation":[54],"diagrams,":[57,204],"which":[58,97,205],"allows":[59],"for":[60,138],"fast":[61,148],"computation":[62],"distances.":[64],"This":[65],"built":[68],"upon":[69],"generative":[71],"adversarial":[72],"network":[73],"(GAN)":[74],"with":[75,201,209,223],"distance":[78],"loss":[79],"function":[80],"steer":[82],"learning":[84],"process.":[85],"Instead":[86],"using":[88,147],"standard":[89],"representations,":[90],"hash":[92],"into":[94],"codes,":[96,144],"natural":[99],"advantages":[100],"large-scale":[102],"tasks.":[103],"The":[104],"training":[105],"model":[108],"domain-oblivious":[110],"it":[113],"can":[114],"be":[115],"computed":[116],"purely":[117],"from":[118],"synthetic,":[119],"randomly":[120],"created":[121],"diagrams.":[122],"As":[123],"consequence,":[125],"our":[126,168,184,196,213,218],"proposed":[127],"method":[128,219],"directly":[130],"applicable":[131],"various":[133],"datasets":[134,157],"without":[135],"need":[137],"retraining":[139],"model.":[141],"These":[142],"when":[145],"compared":[146],"Hamming":[149],"distance,":[150],"better":[151,234],"maintain":[152],"similarity":[154],"properties":[155],"than":[158],"other":[159],"vectorized":[160],"representations.":[161],"To":[162],"evaluate":[163],"method,":[165],"apply":[167],"problem":[172],"clustering":[175],"and":[176,181],"compare":[178],"quality":[180,235],"performance":[182],"approach":[185,197],"state-of-the-art.":[188],"addition,":[190],"show":[192],"scalability":[194],"on":[198],"dataset":[200],"10k":[202],"not":[207],"possible":[208],"current":[210],"techniques.":[211],"Moreover,":[212],"experimental":[214],"results":[215],"demonstrate":[216],"significantly":[221],"faster":[222],"potential":[225],"less":[227],"memory":[228],"usage,":[229],"while":[230],"retaining":[231],"comparable":[232],"or":[233],"comparisons.":[236]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2021-10-11T00:00:00"}
