{"id":"https://openalex.org/W3202797337","doi":"https://doi.org/10.1109/tpami.2022.3226041","title":"Optimising for Interpretability: Convolutional Dynamic Alignment Networks","display_name":"Optimising for Interpretability: Convolutional Dynamic Alignment Networks","publication_year":2022,"publication_date":"2022-12-01","ids":{"openalex":"https://openalex.org/W3202797337","doi":"https://doi.org/10.1109/tpami.2022.3226041","mag":"3202797337","pmid":"https://pubmed.ncbi.nlm.nih.gov/36455090"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3226041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3226041","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2109.13004","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059074320","display_name":"Moritz B\u00f6hle","orcid":"https://orcid.org/0000-0002-5479-3769"},"institutions":[{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Moritz B\u00f6hle","raw_affiliation_strings":["Department of Computer Vision and Machine Learning, Max Planck Institute for Informatics, Saarbr&#x00FC;cken, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5479-3769","affiliations":[{"raw_affiliation_string":"Department of Computer Vision and Machine Learning, Max Planck Institute for Informatics, Saarbr&#x00FC;cken, Germany","institution_ids":["https://openalex.org/I4210109712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003887059","display_name":"Mario Fritz","orcid":"https://orcid.org/0000-0001-8949-9896"},"institutions":[{"id":"https://openalex.org/I4210128801","display_name":"Helmholtz Center for Information Security","ror":"https://ror.org/02njgxr09","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I4210128801"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mario Fritz","raw_affiliation_strings":["CISPA Helmholtz Center for Information Security, Saarbr&#x00FC;cken, Germany"],"raw_orcid":"https://orcid.org/0000-0001-8949-9896","affiliations":[{"raw_affiliation_string":"CISPA Helmholtz Center for Information Security, Saarbr&#x00FC;cken, Germany","institution_ids":["https://openalex.org/I4210128801"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051534545","display_name":"Bernt Schiele","orcid":"https://orcid.org/0000-0001-9683-5237"},"institutions":[{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernt Schiele","raw_affiliation_strings":["Department of Computer Vision and Machine Learning, Max Planck Institute for Informatics, Saarbr&#x00FC;cken, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9683-5237","affiliations":[{"raw_affiliation_string":"Department of Computer Vision and Machine Learning, Max Planck Institute for Informatics, Saarbr&#x00FC;cken, Germany","institution_ids":["https://openalex.org/I4210109712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6561,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72360803,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"45","issue":"6","first_page":"7625","last_page":"7638"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9995999932289124,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983999729156494,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9364650249481201},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7356941103935242},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6620758771896362},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6157753467559814},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6111177206039429},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46346086263656616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4390649199485779},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4250423014163971},{"id":"https://openalex.org/keywords/coda","display_name":"Coda","score":0.42396917939186096},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3255865275859833}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9364650249481201},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7356941103935242},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6620758771896362},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6157753467559814},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6111177206039429},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46346086263656616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4390649199485779},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4250423014163971},{"id":"https://openalex.org/C3962253","wikidata":"https://www.wikidata.org/wiki/Q852466","display_name":"Coda","level":2,"score":0.42396917939186096},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3255865275859833},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2022.3226041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3226041","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:36455090","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36455090","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:2109.13004","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.13004","pdf_url":"https://arxiv.org/pdf/2109.13004","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2109.13004","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.13004","pdf_url":"https://arxiv.org/pdf/2109.13004","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"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1787224781","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W2004026774","https://openalex.org/W2108598243","https://openalex.org/W2123045220","https://openalex.org/W2150165932","https://openalex.org/W2161388792","https://openalex.org/W2194775991","https://openalex.org/W2282821441","https://openalex.org/W2295107390","https://openalex.org/W2594633041","https://openalex.org/W2605409611","https://openalex.org/W2776207810","https://openalex.org/W2809136100","https://openalex.org/W2809671526","https://openalex.org/W2811104224","https://openalex.org/W2891612330","https://openalex.org/W2951603627","https://openalex.org/W2951885001","https://openalex.org/W2953073956","https://openalex.org/W2953133772","https://openalex.org/W2962851944","https://openalex.org/W2962858109","https://openalex.org/W2962862931","https://openalex.org/W2963180316","https://openalex.org/W2963446712","https://openalex.org/W2963703618","https://openalex.org/W2964121744","https://openalex.org/W2964137095","https://openalex.org/W2970852027","https://openalex.org/W2970971581","https://openalex.org/W2975761646","https://openalex.org/W2983358626","https://openalex.org/W3003482062","https://openalex.org/W3034342078","https://openalex.org/W3116286104","https://openalex.org/W3118608800","https://openalex.org/W3156731105","https://openalex.org/W4288359911","https://openalex.org/W4297772692","https://openalex.org/W4300235091","https://openalex.org/W6630875275","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639204139","https://openalex.org/W6677995690","https://openalex.org/W6681608319","https://openalex.org/W6685133223","https://openalex.org/W6716109767","https://openalex.org/W6734194636","https://openalex.org/W6736518430","https://openalex.org/W6737947904","https://openalex.org/W6743446608","https://openalex.org/W6752170072","https://openalex.org/W6753001334","https://openalex.org/W6754669440","https://openalex.org/W6758132781","https://openalex.org/W6767259515","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W1608664830","https://openalex.org/W2047487744","https://openalex.org/W2101702422","https://openalex.org/W2130115884","https://openalex.org/W2140797948","https://openalex.org/W306191460","https://openalex.org/W159997555","https://openalex.org/W2905433371","https://openalex.org/W2389879838","https://openalex.org/W270592066"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,21,54,63],"new":[3],"family":[4],"of":[5,24,65,73,83,99,171],"neural":[6,139],"network":[7,140],"models":[8,125,141],"called":[9],"Convolutional":[10],"Dynamic":[11,32],"Alignment":[12,33],"Networks":[13],"(CoDA":[14],"Nets),":[15],"which":[16,36],"are":[17,31,37,98],"performant":[18,115],"classifiers":[19,145],"with":[20,43,50,91,137],"high":[22,100],"degree":[23],"inherent":[25],"interpretability.":[26],"Their":[27],"core":[28],"building":[29],"blocks":[30],"Units":[34],"(DAUs),":[35],"optimised":[38],"to":[39,121,142,150],"transform":[40],"their":[41],"inputs":[42],"dynamically":[44],"computed":[45],"weight":[46],"vectors":[47],"that":[48,146],"align":[49,90],"task-relevant":[51],"patterns.":[52,94],"As":[53],"result,":[55],"CoDA":[56,112,132],"Nets":[57,113,133],"model":[58],"the":[59,74,81,84,86,163,177],"classification":[60],"prediction":[61],"through":[62],"series":[64],"input-dependent":[66],"linear":[67,71],"transformations,":[68],"allowing":[69],"for":[70],"decomposition":[72],"output":[75,164],"into":[76],"individual":[77],"input":[78,93],"contributions.":[79],"Given":[80],"alignment":[82],"DAUs,":[85],"resulting":[87],"contribution":[88],"maps":[89],"discriminative":[92],"These":[95],"model-inherent":[96],"decompositions":[97],"visual":[101],"quality":[102],"and":[103,123,129],"outperform":[104],"existing":[105],"attribution":[106],"methods":[107],"under":[108],"quantitative":[109],"metrics.":[110],"Further,":[111],"constitute":[114],"classifiers,":[116],"achieving":[117],"on":[118,126],"par":[119],"results":[120],"ResNet":[122],"VGG":[124],"e.g.":[127],"CIFAR-10":[128],"TinyImagenet.":[130],"Lastly,":[131],"can":[134,165],"be":[135,166],"combined":[136],"conventional":[138],"yield":[143],"powerful":[144],"more":[147],"easily":[148],"scale":[149],"complex":[151],"datasets":[152],"such":[153],"as":[154],"Imagenet":[155],"whilst":[156],"exhibiting":[157],"an":[158],"increased":[159],"interpretable":[160],"depth,":[161],"i.e.,":[162],"explained":[167],"well":[168],"in":[169],"terms":[170],"contributions":[172],"from":[173],"intermediate":[174],"layers":[175],"within":[176],"network.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
