{"id":"https://openalex.org/W4220911478","doi":"https://doi.org/10.1145/3487553.3524194","title":"Geometric and Topological Inference for Deep Representations of Complex Networks","display_name":"Geometric and Topological Inference for Deep Representations of Complex Networks","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4220911478","doi":"https://doi.org/10.1145/3487553.3524194"},"language":"en","primary_location":{"id":"doi:10.1145/3487553.3524194","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3487553.3524194","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3487553.3524194","source":{"id":"https://openalex.org/S4363608846","display_name":"Companion Proceedings of the Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the Web Conference 2022","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3487553.3524194","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018612055","display_name":"Baihan Lin","orcid":"https://orcid.org/0000-0002-7979-5509"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Baihan Lin","raw_affiliation_strings":["Columbia University, USA","Columbia University [New York] (Columbia University in the City of New York, 2960 Broadway, New York, NY 10027-6902 - United States)"],"affiliations":[{"raw_affiliation_string":"Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia University [New York] (Columbia University in the City of New York, 2960 Broadway, New York, NY 10027-6902 - United States)","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5018612055"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":1.044,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70717781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"334","last_page":"338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9722999930381775,"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"}},{"id":"https://openalex.org/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9502000212669373,"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/interpretability","display_name":"Interpretability","score":0.8874368071556091},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7138441801071167},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6611558794975281},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.60284823179245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5891112089157104},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5406984090805054},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.5316040515899658},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.503889262676239},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.4962325692176819},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49534645676612854},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4872783422470093},{"id":"https://openalex.org/keywords/topological-data-analysis","display_name":"Topological data analysis","score":0.4831923544406891},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4111570715904236},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.34566113352775574},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.204708993434906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18665584921836853}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8874368071556091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138441801071167},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6611558794975281},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.60284823179245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5891112089157104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5406984090805054},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.5316040515899658},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.503889262676239},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.4962325692176819},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49534645676612854},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4872783422470093},{"id":"https://openalex.org/C2776477805","wikidata":"https://www.wikidata.org/wiki/Q4460773","display_name":"Topological data analysis","level":2,"score":0.4831923544406891},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4111570715904236},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.34566113352775574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.204708993434906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18665584921836853},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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":3,"locations":[{"id":"doi:10.1145/3487553.3524194","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3487553.3524194","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3487553.3524194","source":{"id":"https://openalex.org/S4363608846","display_name":"Companion Proceedings of the Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the Web Conference 2022","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2203.05488","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.05488","pdf_url":"https://arxiv.org/pdf/2203.05488","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":"pmh:oai:HAL:hal-03843112v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03843112","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WWW '22: The ACM Web Conference 2022, Apr 2022, Lyon, France. pp.334-338, &#x27E8;10.1145/3487553.3524194&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":{"id":"doi:10.1145/3487553.3524194","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3487553.3524194","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3487553.3524194","source":{"id":"https://openalex.org/S4363608846","display_name":"Companion Proceedings of the Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the Web Conference 2022","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220911478.pdf","grobid_xml":"https://content.openalex.org/works/W4220911478.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1974803102","https://openalex.org/W1991566301","https://openalex.org/W2125914984","https://openalex.org/W2131774270","https://openalex.org/W2294798173","https://openalex.org/W2337492206","https://openalex.org/W2787262037","https://openalex.org/W2832227888","https://openalex.org/W2888412729","https://openalex.org/W2893054527","https://openalex.org/W2951881727","https://openalex.org/W2957741874","https://openalex.org/W2970420303","https://openalex.org/W3095568355","https://openalex.org/W4200529266","https://openalex.org/W4252023893"],"related_works":["https://openalex.org/W2797441709","https://openalex.org/W2943982549","https://openalex.org/W3203722024","https://openalex.org/W4297660007","https://openalex.org/W2886918272","https://openalex.org/W4387589990","https://openalex.org/W2346578521","https://openalex.org/W4241566321","https://openalex.org/W3101055019","https://openalex.org/W2910028250"],"abstract_inverted_index":{"Understanding":[0],"the":[1,20,29,52,67,96,103,140,145,170,183,199,221],"deep":[2],"representations":[3,101,125],"of":[4,11,22,31,90,98,102,124,132,136,147,169],"complex":[5],"networks":[6],"is":[7],"an":[8,37],"important":[9],"step":[10],"building":[12],"interpretable":[13],"and":[14,86,128,159,172,194,216,228,230],"trustworthy":[15],"machine":[16],"learning":[17],"applications":[18],"in":[19,69,88,106,126,167],"age":[21],"internet.":[23],"Global":[24],"surrogate":[25,62],"models":[26,85,127,190],"that":[27,138,174,202],"approximate":[28],"predictions":[30],"a":[32,61,107,133,207],"black":[33,208],"box":[34,209],"model":[35,53,63,79,108,180],"(e.g.":[36],"artificial":[38],"or":[39,110],"biological":[40],"neural":[41,188],"net)":[42],"are":[43],"usually":[44],"used":[45,178],"to":[46,57,74,118,185,191,195,219,231],"provide":[47],"valuable":[48],"theoretical":[49],"insights":[50],"for":[51,66,78,179,206],"interpretability.":[54],"In":[55,113],"order":[56],"evaluate":[58,164],"how":[59],"well":[60,143],"can":[64],"account":[65,205],"representation":[68],"another":[70],"model,":[71],"we":[72,116],"need":[73],"develop":[75],"inference":[76],"methods":[77,213],"comparison.":[80],"Previous":[81],"studies":[82],"have":[83],"compared":[84],"brains":[87,129,227],"terms":[89,168],"their":[91],"representational":[92,223],"geometries":[93],"(characterized":[94],"by":[95,226],"matrix":[97],"distances":[99],"between":[100],"input":[104],"patterns":[105],"layer":[109],"cortical":[111],"area).":[112],"this":[114],"study,":[115],"propose":[117],"explore":[119],"these":[120,165],"summary":[121,151],"statistical":[122,234],"descriptions":[123],"as":[130,142,144],"part":[131],"broader":[134],"class":[135],"statistics":[137,152,166],"emphasize":[139],"topology":[141],"geometry":[146],"representations.":[148],"The":[149],"topological":[150,155],"build":[153],"on":[154],"data":[156],"analysis":[157],"(TDA)":[158],"other":[160,193],"graph-based":[161],"methods.":[162],"We":[163],"sensitivity":[171],"specificity":[173],"they":[175],"afford":[176],"when":[177],"selection,":[181],"with":[182],"goal":[184],"relate":[186],"different":[187],"network":[189],"each":[192],"make":[196],"inferences":[197],"about":[198],"computational":[200],"mechanism":[201],"might":[203],"best":[204],"representation.":[210],"These":[211],"new":[212],"enable":[214],"brain":[215],"computer":[217],"scientists":[218],"visualize":[220],"dynamic":[222],"transformations":[224],"learned":[225],"models,":[229],"perform":[232],"model-comparative":[233],"inference.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
