{"id":"https://openalex.org/W3205071126","doi":"https://doi.org/10.1137/21m1430194","title":"MGIC: Multigrid-in-Channels Neural Network Architectures","display_name":"MGIC: Multigrid-in-Channels Neural Network Architectures","publication_year":2023,"publication_date":"2023-02-06","ids":{"openalex":"https://openalex.org/W3205071126","doi":"https://doi.org/10.1137/21m1430194","mag":"3205071126"},"language":"en","primary_location":{"id":"doi:10.1137/21m1430194","doi":"https://doi.org/10.1137/21m1430194","is_oa":false,"landing_page_url":"https://doi.org/10.1137/21m1430194","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-a","jufo-3","norway-2","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.09128","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064732307","display_name":"Moshe Eliasof","orcid":"https://orcid.org/0000-0002-1780-2312","observed_orcids":["https://orcid.org/0000-0002-1780-2312"]},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Moshe Eliasof","raw_affiliation_strings":["Corresponding author. Computer Science Department, Ben-Gurion University of the Negev, Beer Sheva, 8410501, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Corresponding author. Computer Science Department, Ben-Gurion University of the Negev, Beer Sheva, 8410501, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018590529","display_name":"Jonathan Ephrath","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Jonathan Ephrath","raw_affiliation_strings":["Computer Science Department, Ben-Gurion University of the Negev, Beer Sheva, 8410501, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Ben-Gurion University of the Negev, Beer Sheva, 8410501, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076591073","display_name":"Lars Ruthotto","orcid":"https://orcid.org/0000-0003-0803-3299","observed_orcids":["https://orcid.org/0000-0003-0803-3299"]},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lars Ruthotto","raw_affiliation_strings":["Departments of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 USA"],"raw_orcid":"https://orcid.org/0000-0003-0803-3299","affiliations":[{"raw_affiliation_string":"Departments of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 USA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042450080","display_name":"Eran Treister","orcid":"https://orcid.org/0000-0002-5351-0966","observed_orcids":["https://orcid.org/0000-0002-5351-0966"]},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Eran Treister","raw_affiliation_strings":["Computer Science Department, Ben-Gurion University of the Negev, Beer Sheva, 8410501, Israel"],"raw_orcid":"https://orcid.org/0000-0002-5351-0966","affiliations":[{"raw_affiliation_string":"Computer Science Department, Ben-Gurion University of the Negev, Beer Sheva, 8410501, Israel","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4421,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.53591078,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":96},"biblio":{"volume":"45","issue":"3","first_page":"S307","last_page":"S328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":9.999999747378752e-05,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.0,"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/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7870000004768372},{"id":"https://openalex.org/keywords/parameter-efficiency","display_name":"parameter efficiency","score":0.7390000224113464},{"id":"https://openalex.org/keywords/channel-redundancy","display_name":"channel redundancy","score":0.4869999885559082},{"id":"https://openalex.org/keywords/group-convolution","display_name":"group convolution","score":0.5580000281333923},{"id":"https://openalex.org/keywords/lightweight-convolutional-neural-network","display_name":"lightweight convolutional neural network","score":0.7080000042915344},{"id":"https://openalex.org/keywords/resnet","display_name":"ResNet","score":0.6129999756813049},{"id":"https://openalex.org/keywords/mobilenetv3","display_name":"MobileNetV3","score":0.9940000176429749},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.9520000219345093},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.8460000157356262},{"id":"https://openalex.org/keywords/point-cloud-classification","display_name":"point cloud classification","score":0.9950000047683716}],"concepts":[{"id":"https://openalex.org/C195956108","wikidata":"https://www.wikidata.org/wiki/Q7268362","display_name":"Quadratic growth","level":2,"score":0.6637870669364929},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6572832465171814},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5525559782981873},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5078056454658508},{"id":"https://openalex.org/C137119250","wikidata":"https://www.wikidata.org/wiki/Q1413101","display_name":"Multigrid method","level":3,"score":0.4823891222476959},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4803256094455719},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.46912217140197754},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4521127939224243},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.44544166326522827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4280169606208801},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.41101783514022827},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40936028957366943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3148472011089325},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12253755331039429},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C93779851","wikidata":"https://www.wikidata.org/wiki/Q271977","display_name":"Partial differential equation","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1137/21m1430194","doi":"https://doi.org/10.1137/21m1430194","is_oa":false,"landing_page_url":"https://doi.org/10.1137/21m1430194","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-a","jufo-3","norway-2","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2011.09128","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.09128","pdf_url":"https://arxiv.org/pdf/2011.09128","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"mag:3102849520","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2011.09128.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2011.09128","doi":"https://doi.org/10.48550/arxiv.2011.09128","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2011.09128","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.09128","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.09128","pdf_url":"https://arxiv.org/pdf/2011.09128","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G150243826","display_name":null,"funder_award_id":"2018209","funder_id":"https://openalex.org/F4320308960","funder_display_name":"United States - Israel Binational Science Foundation"},{"id":"https://openalex.org/G2550295518","display_name":"CAREER: A Flexible Optimal Control Framework for Efficient Training of Deep Neural Networks","funder_award_id":"1751636","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308960","display_name":"United States - Israel Binational Science Foundation","ror":"https://ror.org/00j8z2m73"},{"id":"https://openalex.org/F4704393691","display_name":"Israel Innovation Authority","ror":"https://ror.org/013kba371"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3205071126.pdf","grobid_xml":"https://content.openalex.org/works/W3205071126.grobid-xml"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W1518639170","https://openalex.org/W1636009176","https://openalex.org/W1920022804","https://openalex.org/W1992056335","https://openalex.org/W1997542937","https://openalex.org/W2012630580","https://openalex.org/W2025374807","https://openalex.org/W2048803822","https://openalex.org/W2070448527","https://openalex.org/W2085522030","https://openalex.org/W2089947415","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2137825550","https://openalex.org/W2142304406","https://openalex.org/W2154579312","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2401325911","https://openalex.org/W2468883959","https://openalex.org/W2515385951","https://openalex.org/W2549139847","https://openalex.org/W2553910756","https://openalex.org/W2581531918","https://openalex.org/W2589646680","https://openalex.org/W2593303827","https://openalex.org/W2604388535","https://openalex.org/W2612445135","https://openalex.org/W2616324011","https://openalex.org/W2630837129","https://openalex.org/W2766207105","https://openalex.org/W2776265614","https://openalex.org/W2788421913","https://openalex.org/W2823177849","https://openalex.org/W2883780447","https://openalex.org/W2886851211","https://openalex.org/W2886953980","https://openalex.org/W2889609569","https://openalex.org/W2896409484","https://openalex.org/W2899283552","https://openalex.org/W2899771611","https://openalex.org/W2900501930","https://openalex.org/W2901299405","https://openalex.org/W2902251695","https://openalex.org/W2905741102","https://openalex.org/W2909750748","https://openalex.org/W2912389156","https://openalex.org/W2944779197","https://openalex.org/W2946948417","https://openalex.org/W2949391068","https://openalex.org/W2955419283","https://openalex.org/W2957969499","https://openalex.org/W2963125010","https://openalex.org/W2963145730","https://openalex.org/W2963163009","https://openalex.org/W2963363373","https://openalex.org/W2963382930","https://openalex.org/W2963674932","https://openalex.org/W2963844898","https://openalex.org/W2964137095","https://openalex.org/W2964233199","https://openalex.org/W2967733054","https://openalex.org/W2979750740","https://openalex.org/W2981014499","https://openalex.org/W2982581155","https://openalex.org/W2982619380","https://openalex.org/W2984618279","https://openalex.org/W2988396473","https://openalex.org/W3004424267","https://openalex.org/W3035414587","https://openalex.org/W3103352262","https://openalex.org/W3113272803","https://openalex.org/W3118608800","https://openalex.org/W3122676996","https://openalex.org/W3186990848","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W3102849520","https://openalex.org/W3035588335","https://openalex.org/W4390190178","https://openalex.org/W4308829573","https://openalex.org/W2616324011","https://openalex.org/W3037343903","https://openalex.org/W2912389156","https://openalex.org/W7160850303","https://openalex.org/W2992786536","https://openalex.org/W3210943675"],"abstract_inverted_index":{"Abstract.":[0],"We":[1],"present":[2],"a":[3,86],"multigrid-in-channels":[4],"(MGIC)":[5],"approach":[6,32],"that":[7,38,84,134],"tackles":[8],"the":[9,13,20,34,43,62,70,108,116,146],"quadratic":[10],"growth":[11],"of":[12,15,22,46,64,88,92,115,148],"number":[14,21,63,147],"parameters":[16,149],"with":[17,58,69,80,105],"respect":[18,106],"to":[19,55,96,107,138],"channels":[23,117],"in":[24,36,119],"standard":[25,56,120],"convolutional":[26],"neural":[27],"networks":[28],"(CNNs).":[29],"Thereby":[30],"our":[31,100],"addresses":[33],"redundancy":[35],"CNNs":[37,50,57],"is":[39],"also":[40],"exposed":[41],"by":[42],"recent":[44],"success":[45],"lightweight":[47],"CNNs.":[48,121],"Lightweight":[49],"can":[51],"achieve":[52],"comparable":[53],"accuracy":[54],"fewer":[59],"parameters;":[60],"however,":[61],"weights":[65],"still":[66],"scales":[67],"quadratically":[68],"CNN\u2019s":[71],"width.":[72],"Our":[73,122],"MGIC":[74,82],"architectures":[75,102,140],"replace":[76],"each":[77],"CNN":[78],"block":[79],"an":[81],"counterpart":[83],"utilizes":[85],"hierarchy":[87],"nested":[89],"grouped":[90],"convolutions":[91],"small":[93],"group":[94],"size":[95],"address":[97],"this.":[98],"Hence,":[99],"proposed":[101],"scale":[103],"linearly":[104],"network\u2019s":[109],"width":[110],"while":[111,150],"retaining":[112],"full":[113],"coupling":[114],"as":[118],"extensive":[123],"experiments":[124],"on":[125],"image":[126],"classification,":[127],"segmentation,":[128],"and":[129,143],"point":[130],"cloud":[131],"classification":[132],"show":[133],"applying":[135],"this":[136],"strategy":[137],"different":[139],"like":[141],"ResNet":[142],"MobileNetV3":[144],"reduces":[145],"obtaining":[151],"similar":[152],"or":[153],"better":[154],"accuracy.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2021-10-25T00:00:00"}
