{"id":"https://openalex.org/W4389161127","doi":"https://doi.org/10.1109/tc.2023.3337319","title":"Approximation- and Quantization-Aware Training for Graph Neural Networks","display_name":"Approximation- and Quantization-Aware Training for Graph Neural Networks","publication_year":2023,"publication_date":"2023-11-30","ids":{"openalex":"https://openalex.org/W4389161127","doi":"https://doi.org/10.1109/tc.2023.3337319"},"language":"en","primary_location":{"id":"doi:10.1109/tc.2023.3337319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2023.3337319","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","1557-9956","2326-3814"],"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 Computers","raw_type":"journal-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/A5040754880","display_name":"Rodion Novkin","orcid":"https://orcid.org/0009-0006-6632-9804"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Rodion Novkin","raw_affiliation_strings":["Chair of AI Processor Design, TUM School of Computation, Information and Technology and Munich Institute of Robotics and Machine Intelligence, Technical University of Munich (TUM), Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of AI Processor Design, TUM School of Computation, Information and Technology and Munich Institute of Robotics and Machine Intelligence, Technical University of Munich (TUM), Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083905801","display_name":"Florian Klemme","orcid":"https://orcid.org/0000-0002-0148-0523"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florian Klemme","raw_affiliation_strings":["Semiconductor Test and Reliability (STAR), University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Semiconductor Test and Reliability (STAR), University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059133190","display_name":"Hussam Amrouch","orcid":"https://orcid.org/0000-0002-5649-3102"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hussam Amrouch","raw_affiliation_strings":["Chair of AI Processor Design, TUM School of Computation, Information and Technology and Munich Institute of Robotics and Machine Intelligence, Technical University of Munich (TUM), Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of AI Processor Design, TUM School of Computation, Information and Technology and Munich Institute of Robotics and Machine Intelligence, Technical University of Munich (TUM), Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040754880"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":2.2728,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90661788,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"73","issue":"2","first_page":"599","last_page":"612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9984999895095825,"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":0.9984999895095825,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7370572686195374},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6201210021972656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4746863543987274},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.46148672699928284},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44835788011550903},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42267102003097534},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37551233172416687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3694075047969818}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7370572686195374},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6201210021972656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4746863543987274},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.46148672699928284},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44835788011550903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42267102003097534},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37551233172416687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3694075047969818}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tc.2023.3337319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2023.3337319","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","1557-9956","2326-3814"],"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 Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2914956538","display_name":null,"funder_award_id":"428566201","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1966797259","https://openalex.org/W1996431812","https://openalex.org/W2054095206","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2242818861","https://openalex.org/W2294851045","https://openalex.org/W2533121491","https://openalex.org/W2776622059","https://openalex.org/W2788284887","https://openalex.org/W2899084402","https://openalex.org/W2903222888","https://openalex.org/W2907492528","https://openalex.org/W2944333218","https://openalex.org/W2958306322","https://openalex.org/W2962711740","https://openalex.org/W2963312446","https://openalex.org/W2963396480","https://openalex.org/W2964015378","https://openalex.org/W2964266063","https://openalex.org/W3007372856","https://openalex.org/W3036274717","https://openalex.org/W3036417437","https://openalex.org/W3037801075","https://openalex.org/W3042313988","https://openalex.org/W3044450160","https://openalex.org/W3048414096","https://openalex.org/W3098766148","https://openalex.org/W3117528324","https://openalex.org/W3127829048","https://openalex.org/W3137147200","https://openalex.org/W3141007974","https://openalex.org/W3176940011","https://openalex.org/W4220829081","https://openalex.org/W4221106024","https://openalex.org/W4288419263","https://openalex.org/W4304693398","https://openalex.org/W4308090233","https://openalex.org/W4312121107","https://openalex.org/W4378509449","https://openalex.org/W6690026940","https://openalex.org/W6699364125","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6751350349","https://openalex.org/W6754929296","https://openalex.org/W6760045743","https://openalex.org/W6763676199","https://openalex.org/W6780444311","https://openalex.org/W6781376665","https://openalex.org/W6853251322"],"related_works":["https://openalex.org/W2114837856","https://openalex.org/W2979160909","https://openalex.org/W2961085424","https://openalex.org/W2359364609","https://openalex.org/W2391251536","https://openalex.org/W4386322429","https://openalex.org/W2362198218","https://openalex.org/W3212911258","https://openalex.org/W3206280435","https://openalex.org/W2952965081"],"abstract_inverted_index":{"Graph":[0],"Neural":[1,32],"Networks":[2,33],"(GNNs)":[3],"are":[4,15],"one":[5],"of":[6,26,44,61,117,132,147,178],"the":[7,23,52,59,76,100,115,125,145],"best-performing":[8],"models":[9],"for":[10,37,48,75,93,165,171],"processing":[11],"graph":[12,54,166],"data.":[13],"They":[14],"known":[16],"to":[17,29,95,112],"have":[18],"considerable":[19],"computational":[20],"complexity,":[21],"despite":[22],"smaller":[24],"number":[25],"parameters":[27],"compared":[28],"traditional":[30],"Deep":[31],"(DNNs).":[34],"Operations-to-parameters":[35],"ratio":[36],"GNNs":[38,66,94,133],"can":[39],"be":[40],"tens":[41],"and":[42,70,83,88,129,155,160,169],"hundreds":[43],"times":[45],"higher":[46],"than":[47],"DNNs,":[49],"depending":[50],"on":[51,157],"input":[53],"size.":[55],"This":[56],"complexity":[57],"indicates":[58],"importance":[60],"arithmetic":[62],"operation":[63],"optimization":[64],"within":[65,120],"through":[67],"model":[68],"quantization":[69],"approximation.":[71],"In":[72],"this":[73],"work,":[74],"first":[77],"time,":[78],"we":[79,123],"combine":[80],"both":[81],"approaches":[82],"implement":[84],"<italic":[85,89],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[86,90,187],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">quantization-</i>":[87],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">approximation-aware":[91],"training</i>":[92],"sustain":[96],"their":[97],"accuracy":[98],"under":[99],"errors":[101],"induced":[102],"by":[103],"inexact":[104],"multiplications.":[105],"We":[106,143],"employ":[107],"matrix":[108],"multiplication":[109,119],"CUDA":[110],"kernel":[111],"speed":[113],"up":[114],"simulation":[116],"approximate":[118,135,179],"GNNs.":[121,142],"Further,":[122],"demonstrate":[124],"execution":[126],"speed,":[127],"accuracy,":[128],"energy":[130],"efficiency":[131],"with":[134,139,174],"multipliers":[136],"in":[137],"comparison":[138],"quantized":[140],"low-bit":[141],"evaluate":[144],"performance":[146],"state-of-the-art":[148],"GNN":[149],"architectures":[150],"(i.e.,":[151,162],"GIN,":[152],"SAGE,":[153],"GCN,":[154],"GAT)":[156],"various":[158],"datasets":[159],"tasks":[161],"Reddit-Binary,":[163],"Collab":[164],"classification,":[167],"Cora":[168],"PubMed":[170],"node":[172],"classification)":[173],"a":[175],"wide":[176],"range":[177],"multipliers.":[180],"Our":[181],"framework":[182],"is":[183],"available":[184],"online:":[185],"<uri":[186],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/TUM-AIPro/AxC-GNN</uri>":[188],".":[189]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
