{"id":"https://openalex.org/W4285596889","doi":"https://doi.org/10.48550/arxiv.2207.06741","title":"Differentiable Logics for Neural Network Training and Verification","display_name":"Differentiable Logics for Neural Network Training and Verification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285596889","doi":"https://doi.org/10.48550/arxiv.2207.06741"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2207.06741","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2207.06741","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065519694","display_name":"Natalia Slusarz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Slusarz, Natalia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026643182","display_name":"Ekaterina Komendantskaya","orcid":"https://orcid.org/0000-0002-3240-0987"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Komendantskaya, Ekaterina","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006770740","display_name":"Matthew L. Daggitt","orcid":"https://orcid.org/0000-0002-2552-3671"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daggitt, Matthew L.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067147989","display_name":"Robert Stewart","orcid":"https://orcid.org/0000-0002-4435-6397"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stewart, Robert","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9523,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9523,"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":[],"concepts":[{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.7700001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6815997},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6507887},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.61432916},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5368673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47025573},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45068},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.43513206},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36020485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19684717},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.08371514},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2207.06741","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2207.06741","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2207.06741","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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4327738859","https://openalex.org/W4286826125","https://openalex.org/W4285277090","https://openalex.org/W3181683615","https://openalex.org/W2348722996","https://openalex.org/W2334570605","https://openalex.org/W2115878407","https://openalex.org/W1980454230","https://openalex.org/W1633485514","https://openalex.org/W1604739066"],"abstract_inverted_index":{"The":[0],"rising":[1],"popularity":[2],"of":[3,23,69,155,166,172,187,189],"neural":[4,55,129],"networks":[5,56],"(NNs)":[6],"in":[7,14,43,49,169],"recent":[8],"years":[9],"and":[10,100,201],"their":[11,24],"increasing":[12],"prevalence":[13],"real-world":[15],"applications":[16],"have":[17,37],"drawn":[18],"attention":[19],"to":[20,30,64,72,77,82,90,95,127,138],"the":[21,50,74,96,170,177,185,190],"importance":[22],"verification.":[25,101],"While":[26],"verification":[27],"is":[28,71,87,106],"known":[29],"be":[31,139],"computationally":[32],"difficult":[33],"theoretically,":[34],"many":[35],"techniques":[36],"been":[38,47],"proposed":[39],"for":[40,112,132,180],"solving":[41],"it":[42],"practice.":[44],"It":[45],"has":[46],"observed":[48],"literature":[51],"that":[52,61],"by":[53,108],"default":[54],"rarely":[57],"satisfy":[58,78],"logical":[59],"constraints":[60,105],"we":[62,198],"want":[63],"verify.":[65],"A":[66],"good":[67],"course":[68],"action":[70],"train":[73,128],"given":[75,114],"NN":[76],"said":[79],"constraint":[80],"prior":[81],"verifying":[83],"them.":[84],"This":[85,148],"idea":[86],"sometimes":[88],"referred":[89],"as":[91],"continuous":[92,173],"verification,":[93],"referring":[94],"loop":[97],"between":[98],"training":[99,103,133],"Usually":[102],"with":[104],"implemented":[107],"specifying":[109],"a":[110,113,163,181],"translation":[111],"formal":[115],"logic":[116],"language":[117],"into":[118],"loss":[119,122,192],"functions.":[120],"These":[121],"functions":[123,136],"are":[124,143,158,176],"then":[125],"used":[126],"networks.":[130],"Because":[131],"purposes":[134],"these":[135,141,203],"need":[137],"differentiable,":[140],"translations":[142],"called":[144],"differentiable":[145,156],"logics":[146,157],"(DL).":[147],"raises":[149],"several":[150],"research":[151],"questions.":[152,204],"What":[153,160,175],"kind":[154],"possible?":[159],"difference":[161],"does":[162],"specific":[164],"choice":[165],"DL":[167,182],"make":[168],"context":[171],"verification?":[174],"desirable":[178],"criteria":[179],"viewed":[183],"from":[184],"point":[186],"view":[188],"resulting":[191],"function?":[193],"In":[194],"this":[195],"extended":[196],"abstract":[197],"will":[199],"discuss":[200],"answer":[202]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4285596889","counts_by_year":[],"updated_date":"2024-12-07T04:45:14.449992","created_date":"2022-07-16"}