{"id":"https://openalex.org/W3186879587","doi":null,"title":"How to Tell Deep Neural Networks What We Know.","display_name":"How to Tell Deep Neural Networks What We Know.","publication_year":2021,"publication_date":"2021-07-21","ids":{"openalex":"https://openalex.org/W3186879587","mag":"3186879587"},"language":"en","primary_location":{"id":"mag:3186879587","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2107.10295","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},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2107.10295","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043196180","display_name":"Tirtharaj Dash","orcid":"https://orcid.org/0000-0001-5965-8286","observed_orcids":["https://orcid.org/0000-0001-5965-8286"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tirtharaj Dash","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-5965-8286","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037225297","display_name":"Sharad Chitlangia","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharad Chitlangia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011038695","display_name":"Aditya Ahuja","orcid":"https://orcid.org/0000-0003-4404-0461","observed_orcids":["https://orcid.org/0000-0003-4404-0461"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aditya Ahuja","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4404-0461","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103083219","display_name":"Ashwin Srinivasan","orcid":"https://orcid.org/0000-0002-4911-0038","observed_orcids":["https://orcid.org/0000-0002-4911-0038"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ashwin Srinivasan","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4911-0038","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.5181000232696533,"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/T10320","display_name":"Neural Networks and Applications","score":0.5181000232696533,"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":0.2992999851703644,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.04039999842643738,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/domain-knowledge-integration","display_name":"domain knowledge integration","score":0.7789999842643738},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.9440000057220459},{"id":"https://openalex.org/keywords/human-machine-collaboration","display_name":"human-machine collaboration","score":0.6819999814033508},{"id":"https://openalex.org/keywords/scientific-knowledge","display_name":"scientific knowledge","score":0.5659999847412109},{"id":"https://openalex.org/keywords/loss-functions","display_name":"loss functions","score":0.7179999947547913},{"id":"https://openalex.org/keywords/network-architecture","display_name":"network architecture","score":0.6620000004768372},{"id":"https://openalex.org/keywords/input-encoding","display_name":"input encoding","score":0.7149999737739563},{"id":"https://openalex.org/keywords/scientific-assistants","display_name":"scientific assistants","score":0.6269999742507935},{"id":"https://openalex.org/keywords/knowledge-guided-learning","display_name":"knowledge-guided learning","score":0.4519999921321869}],"concepts":[{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6769453287124634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6717959642410278},{"id":"https://openalex.org/C2776285698","wikidata":"https://www.wikidata.org/wiki/Q2642214","display_name":"Exposition (narrative)","level":2,"score":0.6712298393249512},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6600285768508911},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.6324533224105835},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5614162683486938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5431872606277466},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5050321221351624},{"id":"https://openalex.org/C109359841","wikidata":"https://www.wikidata.org/wiki/Q728944","display_name":"Inclusion (mineral)","level":2,"score":0.4920884966850281},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.44093823432922363},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4090721011161804},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11917167901992798},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08780524134635925},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.08669689297676086},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.07062599062919617},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3186879587","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2107.10295","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}],"best_oa_location":{"id":"mag:3186879587","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2107.10295","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},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1552847225","https://openalex.org/W1821462560","https://openalex.org/W1899864426","https://openalex.org/W1986767090","https://openalex.org/W1993845689","https://openalex.org/W2046595011","https://openalex.org/W2099034483","https://openalex.org/W2159660112","https://openalex.org/W2201744460","https://openalex.org/W2439568532","https://openalex.org/W2460053120","https://openalex.org/W2563063592","https://openalex.org/W2727300753","https://openalex.org/W2766151966","https://openalex.org/W2767656849","https://openalex.org/W2770392471","https://openalex.org/W2784186414","https://openalex.org/W2888684310","https://openalex.org/W2890273554","https://openalex.org/W2907083460","https://openalex.org/W2923924002","https://openalex.org/W2963687836","https://openalex.org/W2964306570","https://openalex.org/W2970236742","https://openalex.org/W2971954582","https://openalex.org/W2981731882","https://openalex.org/W2989771576","https://openalex.org/W3007528869","https://openalex.org/W3008128620","https://openalex.org/W3008914533","https://openalex.org/W3030163527","https://openalex.org/W3034789704","https://openalex.org/W3094736108","https://openalex.org/W3127779731","https://openalex.org/W3162220519","https://openalex.org/W3164003584"],"related_works":["https://openalex.org/W3210202898","https://openalex.org/W4205511145","https://openalex.org/W4394663366","https://openalex.org/W2913159621","https://openalex.org/W4287722672","https://openalex.org/W2158476197","https://openalex.org/W114664117","https://openalex.org/W2747981372","https://openalex.org/W3213664599","https://openalex.org/W2911240635"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,66,103],"short":[3],"survey":[4],"of":[5,22,25,61,75,79,89,97,105],"ways":[6],"in":[7,65,99,125],"which":[8],"existing":[9],"scientific":[10,32],"knowledge":[11],"are":[12],"included":[13],"when":[14],"constructing":[15,31],"models":[16],"with":[17,59],"neural":[18],"networks.":[19,91],"The":[20,92],"inclusion":[21,74],"domain-knowledge":[23,76],"is":[24,94],"special":[26],"interest":[27],"not":[28],"just":[29],"to":[30,121],"assistants,":[33],"but":[34],"also,":[35],"many":[36,47],"other":[37],"areas":[38],"that":[39,117],"involve":[40],"understanding":[41],"data":[42],"using":[43],"human-machine":[44],"collaboration.":[45],"In":[46,111],"such":[48,106],"instances,":[49],"machine-based":[50],"model":[51],"construction":[52],"may":[53],"benefit":[54],"significantly":[55],"from":[56],"being":[57],"provided":[58],"human-knowledge":[60],"the":[62,73,82,84,87],"domain":[63],"encoded":[64],"sufficiently":[67],"precise":[68],"form.":[69],"This":[70],"paper":[71],"examines":[72],"by":[77],"means":[78],"changes":[80,107,124],"to:":[81],"input,":[83],"loss-function,":[85],"and":[86],"architecture":[88],"deep":[90],"categorisation":[93],"for":[95],"ease":[96],"exposition:":[98],"practice":[100],"we":[101,114],"expect":[102],"combination":[104],"will":[108],"be":[109],"employed.":[110],"each":[112],"category,":[113],"describe":[115],"techniques":[116],"have":[118],"been":[119],"shown":[120],"yield":[122],"significant":[123],"network":[126],"performance.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2021-08-02T00:00:00"}
