{"id":"https://openalex.org/W3213430165","doi":"https://doi.org/10.1109/mlsp52302.2021.9596206","title":"Dynamic Graph Convolutional Network: A Topology Optimization Perspective","display_name":"Dynamic Graph Convolutional Network: A Topology Optimization Perspective","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W3213430165","doi":"https://doi.org/10.1109/mlsp52302.2021.9596206","mag":"3213430165"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp52302.2021.9596206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5019923149","display_name":"Bowen Deng","orcid":"https://orcid.org/0000-0003-1447-842X"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bowen Deng","raw_affiliation_strings":["College of Internet of Things Engineering, Hohai University, ChangZhou, China"],"affiliations":[{"raw_affiliation_string":"College of Internet of Things Engineering, Hohai University, ChangZhou, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028119374","display_name":"Aimin Jiang","orcid":"https://orcid.org/0000-0002-9181-934X"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aimin Jiang","raw_affiliation_strings":["College of Internet of Things Engineering, Hohai University, ChangZhou, China"],"affiliations":[{"raw_affiliation_string":"College of Internet of Things Engineering, Hohai University, ChangZhou, China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019923149"],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56608309,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.731010913848877},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6246759295463562},{"id":"https://openalex.org/keywords/topological-graph-theory","display_name":"Topological graph theory","score":0.5447580814361572},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.5023596286773682},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47801005840301514},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.4738614559173584},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.41432759165763855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3230544924736023},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.2298286259174347},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.1745094358921051},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1681366264820099},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11064285039901733}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.731010913848877},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6246759295463562},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.5447580814361572},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.5023596286773682},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47801005840301514},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.4738614559173584},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.41432759165763855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3230544924736023},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.2298286259174347},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.1745094358921051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1681366264820099},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11064285039901733},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp52302.2021.9596206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp52302.2021.9596206","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3466844949","display_name":null,"funder_award_id":"2018AAA0100800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7349900714","display_name":null,"funder_award_id":"2018B23014,2018B47114","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1662382123","https://openalex.org/W2153959628","https://openalex.org/W2194775991","https://openalex.org/W2624431344","https://openalex.org/W2803831897","https://openalex.org/W2804057010","https://openalex.org/W2900763475","https://openalex.org/W2918342466","https://openalex.org/W2963858333","https://openalex.org/W2964015378","https://openalex.org/W2964114465","https://openalex.org/W2964121744","https://openalex.org/W2964311892","https://openalex.org/W2966149470","https://openalex.org/W2971328361","https://openalex.org/W2978508283","https://openalex.org/W2995914187","https://openalex.org/W2998496395","https://openalex.org/W3005104128","https://openalex.org/W3034492151","https://openalex.org/W4288335984","https://openalex.org/W4288419263","https://openalex.org/W4289389616","https://openalex.org/W4297733535","https://openalex.org/W6631190155","https://openalex.org/W6637178625","https://openalex.org/W6726873649","https://openalex.org/W6745537798","https://openalex.org/W6752110883","https://openalex.org/W6755863455","https://openalex.org/W6763882751","https://openalex.org/W6768314895","https://openalex.org/W6779961489"],"related_works":["https://openalex.org/W2086397253","https://openalex.org/W2133122801","https://openalex.org/W600422426","https://openalex.org/W2007156430","https://openalex.org/W3081478936","https://openalex.org/W2785612136","https://openalex.org/W2099529706","https://openalex.org/W1988224651","https://openalex.org/W2096179639","https://openalex.org/W2560916850"],"abstract_inverted_index":{"Recently,":[0],"graph":[1,23,76,95,104,130],"convolutional":[2],"networks(GCNs)":[3],"have":[4],"drawn":[5],"increasing":[6],"attention":[7],"in":[8,19,47,94,99,179],"many":[9,180],"domains,":[10],"e.g.,":[11],"social":[12],"networks,":[13],"recommendation":[14],"systems.":[15],"It's":[16],"known":[17],"that,":[18],"the":[20,35,40,50,68,74,154,158,167],"task":[21],"of":[22,49,73],"node":[24,60],"classification,":[25],"inter-class":[26],"edges":[27],"connecting":[28],"nodes":[29],"from":[30],"different":[31],"categories":[32],"often":[33,84],"degrade":[34],"GCN":[36,64,149],"model":[37],"performance.":[38],"On":[39],"other":[41,147],"hand,":[42],"a":[43,102,138],"stronger":[44],"intra-class":[45],"connection":[46],"terms":[48],"edge":[51,54,71,109,119],"number":[52],"and":[53,70,86,170],"weights":[55,72,110],"is":[56,123,136],"always":[57],"beneficial":[58],"to":[59,151],"classification.":[61],"Most":[62],"existing":[63],"models":[65,150],"assume":[66],"that":[67,128,141,166],"topology":[69,131],"underlying":[75],"are":[77,83,111],"both":[78],"fixed.":[79],"However,":[80],"real-world":[81],"networks":[82],"noisy":[85],"incomplete.":[87],"To":[88],"take":[89],"into":[90],"account":[91],"such":[92,127],"uncertainty":[93],"topology,":[96],"we":[97],"propose":[98],"this":[100],"paper":[101],"dynamic":[103],"convolution":[105],"network":[106,159],"(DyGCN),":[107],"where":[108],"treated":[112],"as":[113],"learnable":[114],"parameters.":[115],"A":[116],"novel":[117],"adaptive":[118],"dropping":[120],"(AdaDrop)":[121],"strategy":[122],"developed":[124],"for":[125],"DyGCN,":[126],"even":[129],"can":[132,142,174],"be":[133,143],"optimized.":[134],"DyGCN":[135,169],"also":[137],"flexible":[139],"architecture":[140],"readily":[144],"combined":[145],"with":[146,153],"deep":[148,172],"cope":[152],"oversmoothness":[155],"encountered":[156],"when":[157],"goes":[160],"very":[161],"deep.":[162],"Experimental":[163],"results":[164],"demonstrate":[165],"proposed":[168],"its":[171],"variants":[173],"achieve":[175],"competitive":[176],"classification":[177],"accuracy":[178],"datasets.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}