{"id":"https://openalex.org/W4415111087","doi":"https://doi.org/10.1109/tsp.2026.3687632","title":"Directed Acyclic Graph Convolutional Networks","display_name":"Directed Acyclic Graph Convolutional Networks","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4415111087","doi":"https://doi.org/10.1109/tsp.2026.3687632"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2026.3687632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2026.3687632","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.12218","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001628625","display_name":"Samuel Rey","orcid":"https://orcid.org/0000-0003-1208-8997"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Samuel Rey","raw_affiliation_strings":["Department of Signal Theory and Communications, Rey Juan Carlos University, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0003-1208-8997","affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, Rey Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5096912326","display_name":"Hamed Ajorlou","orcid":null},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamed Ajorlou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA"],"raw_orcid":"https://orcid.org/0009-0002-6271-6058","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006078163","display_name":"Gonzalo Mateos","orcid":"https://orcid.org/0000-0002-9847-6298"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gonzalo Mateos","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-9847-6298","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01040677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"74","issue":null,"first_page":"1847","last_page":"1862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.965399980545044,"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":0.965399980545044,"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":0.9333999752998352,"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/T11476","display_name":"Graph theory and applications","score":0.916100025177002,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.8513000011444092},{"id":"https://openalex.org/keywords/expressive-power","display_name":"Expressive power","score":0.5501000285148621},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5414999723434448},{"id":"https://openalex.org/keywords/permutation","display_name":"Permutation (music)","score":0.5400000214576721},{"id":"https://openalex.org/keywords/directed-graph","display_name":"Directed graph","score":0.5320000052452087},{"id":"https://openalex.org/keywords/topological-sorting","display_name":"Topological sorting","score":0.5146999955177307},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5056999921798706},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45500001311302185}],"concepts":[{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.8513000011444092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7361999750137329},{"id":"https://openalex.org/C195818886","wikidata":"https://www.wikidata.org/wiki/Q5421724","display_name":"Expressive power","level":2,"score":0.5501000285148621},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.5400000214576721},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.5320000052452087},{"id":"https://openalex.org/C176032523","wikidata":"https://www.wikidata.org/wiki/Q753127","display_name":"Topological sorting","level":3,"score":0.5146999955177307},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5095999836921692},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5056999921798706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4952999949455261},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45500001311302185},{"id":"https://openalex.org/C197352929","wikidata":"https://www.wikidata.org/wiki/Q1074074","display_name":"Inductive bias","level":4,"score":0.36579999327659607},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.33239999413490295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31279999017715454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2935999929904938},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.26589998602867126}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tsp.2026.3687632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2026.3687632","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2506.12218","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.12218","pdf_url":"https://arxiv.org/pdf/2506.12218","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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:arXiv.org:2506.12218","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2506.12218","pdf_url":"https://arxiv.org/pdf/2506.12218","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.12218","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.12218","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.12218","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.12218","pdf_url":"https://arxiv.org/pdf/2506.12218","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1851895436","display_name":null,"funder_award_id":"PID2022-136887NB-I00","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G1976328470","display_name":null,"funder_award_id":"TEC-2024/COM-89","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G3417115895","display_name":null,"funder_award_id":"CAM-URJC F1180 (CP2301)","funder_id":"https://openalex.org/F4320313831","funder_display_name":"Comunidad de Madrid"},{"id":"https://openalex.org/G3855493365","display_name":null,"funder_award_id":"PID2023-149457OB","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G41449784","display_name":null,"funder_award_id":"PID2023-149457OB-I00","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G4326979183","display_name":null,"funder_award_id":"PID2023-149457OB-I00","funder_id":"https://openalex.org/F4320324496","funder_display_name":"Universidad Rey Juan Carlos"},{"id":"https://openalex.org/G464105488","display_name":null,"funder_award_id":"PID2023","funder_id":"https://openalex.org/F4320335598","funder_display_name":"Agencia Estatal de Investigaci\u00f3n"},{"id":"https://openalex.org/G6827728857","display_name":null,"funder_award_id":"TEC-2024","funder_id":"https://openalex.org/F4320313831","funder_display_name":"Comunidad de Madrid"},{"id":"https://openalex.org/G8584220281","display_name":"ASCENT: Using Optical Frequency Comb for Ultrafast Nature-Based Computing for Machine Learning Algorithms","funder_award_id":"2231036","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G873222275","display_name":null,"funder_award_id":"TEC-2024/COM-89","funder_id":"https://openalex.org/F4320313831","funder_display_name":"Comunidad de Madrid"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320313831","display_name":"Comunidad de Madrid","ror":null},{"id":"https://openalex.org/F4320324496","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687"},{"id":"https://openalex.org/F4320335598","display_name":"Agencia Estatal de Investigaci\u00f3n","ror":null},{"id":"https://openalex.org/F4320337392","display_name":"Division of Electrical, Communications and Cyber Systems","ror":"https://ror.org/01krpsy48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Directed":[0],"acyclic":[1],"graphs":[2],"(DAGs)":[3],"are":[4,151],"central":[5],"to":[6,57,68,111],"science":[7],"and":[8,15,119,147,161,177],"engineering":[9],"applications":[10],"including":[11],"causal":[12,54,116],"inference,":[13],"scheduling,":[14],"the":[16,27,64,100],"automated":[17],"design":[18],"of":[19,115,174],"neural":[20,35],"architectures.":[21],"In":[22],"this":[23],"work,":[24],"we":[25],"introduce":[26],"DAG":[28,109],"Convolutional":[29],"Network":[30],"(DCN),":[31],"a":[32,70,104,112,125,185],"novel":[33],"graph":[34,55,136],"network":[36],"(GNN)":[37],"architecture":[38],"designed":[39,196],"specifically":[40],"for":[41,63,188],"<italic":[42],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[43],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">convolutional</i>":[44],"learning":[45,84,190],"from":[46,135,191,197],"signals":[47,110],"supported":[48],"on":[49,89],"DAGs.":[50],"The":[51,143],"DCN":[52,87,102],"leverages":[53],"filters":[56],"learn":[58],"nodal":[59],"representations":[60],"that":[61,93,106,165,194],"account":[62],"partial":[65],"ordering":[66],"inherent":[67],"DAGs,":[69,86],"strong":[71],"inductive":[72],"bias":[73],"not":[74],"present":[75],"in":[76,82,172],"conventional":[77],"GNNs.":[78],"Unlike":[79],"prior":[80],"art":[81],"machine":[83],"over":[85],"builds":[88],"formal":[90],"convolutional":[91],"operations":[92],"admit":[94],"spectraldomain":[95],"representations.":[96],"We":[97],"further":[98],"propose":[99],"Parallel":[101],"(PDCN),":[103],"model":[105,133],"feeds":[107],"input":[108],"parallel":[113],"bank":[114],"graph-shift":[117],"operators":[118],"processes":[120],"these":[121],"DAG-aware":[122],"features":[123],"using":[124],"shared":[126],"multilayer":[127],"perceptron.":[128],"This":[129],"way,":[130],"PDCN":[131],"decouples":[132],"complexity":[134],"size":[137],"while":[138],"maintaining":[139],"satisfactory":[140],"predictive":[141],"performance.":[142],"architectures\u2019":[144],"permutation":[145],"equivariance":[146],"expressive":[148],"power":[149],"properties":[150],"also":[152],"established.":[153],"Comprehensive":[154],"numerical":[155],"tests":[156],"across":[157],"several":[158],"tasks,":[159],"datasets,":[160],"experimental":[162],"conditions":[163],"demonstrate":[164],"(P)DCN":[166,183],"compares":[167],"favorably":[168],"with":[169],"state-of-the-art":[170],"baselines":[171],"terms":[173],"accuracy,":[175],"robustness,":[176],"computational":[178],"efficiency.":[179],"These":[180],"results":[181],"position":[182],"as":[184],"viable":[186],"framework":[187],"deep":[189],"DAG-structured":[192],"data":[193],"is":[195],"first":[198],"(graph)":[199],"signal":[200],"processing":[201],"principles.":[202]},"counts_by_year":[],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-13T00:00:00"}
