{"id":"https://openalex.org/W4381573093","doi":"https://doi.org/10.48550/arxiv.2306.11161","title":"Neuro-Symbolic Bi-Directional Translation -- Deep Learning Explainability for Climate Tipping Point Research","display_name":"Neuro-Symbolic Bi-Directional Translation -- Deep Learning Explainability for Climate Tipping Point Research","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4381573093","doi":"https://doi.org/10.48550/arxiv.2306.11161"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2306.11161","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/2306.11161","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028530447","display_name":"Chace Ashcraft","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ashcraft, Chace","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020969830","display_name":"Jennifer Sleeman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sleeman, Jennifer","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017795133","display_name":"Caroline Tang","orcid":"https://orcid.org/0000-0001-7966-5854"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Caroline","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069885894","display_name":"Jay Brett","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brett, Jay","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5024290744","display_name":"Anand Gnanadesikan","orcid":"https://orcid.org/0000-0001-5784-1116"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gnanadesikan, Anand","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":67},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.983,"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":0.983,"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/T10028","display_name":"Topic Modeling","score":0.9763,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.965,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.80925286},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.7187922}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.80925286},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7238554},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.7187922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6751759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6558627},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47699505},{"id":"https://openalex.org/C168754636","wikidata":"https://www.wikidata.org/wiki/Q620920","display_name":"Climate model","level":3,"score":0.45468757},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3993719},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.26164734},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.15476623},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.087355256},{"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2306.11161","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.11161","pdf_url":"http://arxiv.org/pdf/2306.11161","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2306.11161","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/2306.11161","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.8,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4390569940","https://openalex.org/W4388422664","https://openalex.org/W4361193272","https://openalex.org/W4312407344","https://openalex.org/W4310278675","https://openalex.org/W2963326959","https://openalex.org/W2905433371","https://openalex.org/W2894289927","https://openalex.org/W2888392564","https://openalex.org/W2806259446"],"abstract_inverted_index":{"In":[0,71],"recent":[1],"years,":[2],"there":[3],"has":[4,45],"been":[5,20,46],"an":[6],"increase":[7],"in":[8],"using":[9],"deep":[10,26,69,92,132],"learning":[11,27,93,133],"for":[12,91,153],"climate":[13,94,98,122,129],"and":[14,23,43,66,89,115,131,144,149],"weather":[15],"modeling.":[16],"Though":[17],"results":[18,139],"have":[19],"impressive,":[21],"explainability":[22,88],"interpretability":[24,90],"of":[25,36,61,64,140,161],"models":[28],"are":[29],"still":[30],"a":[31,49,58,76,106,126,146,154],"challenge.":[32],"A":[33],"third":[34],"wave":[35],"Artificial":[37],"Intelligence":[38],"(AI),":[39],"which":[40],"includes":[41,105],"logic":[42,65],"reasoning,":[44],"described":[47],"as":[48,125],"way":[50],"to":[51,86,97,119],"address":[52,87],"these":[53],"issues.":[54],"Neuro-symbolic":[55],"AI":[56],"is":[57],"key":[59],"component":[60],"this":[62,72,141],"integration":[63],"reasoning":[67],"with":[68],"learning.":[70],"work":[73],"we":[74],"propose":[75],"neuro-symbolic":[77],"approach":[78],"called":[79],"Neuro-Symbolic":[80],"Question-Answer":[81],"Program":[82],"Translator,":[83],"or":[84],"NS-QAPT,":[85],"simulation,":[95,123],"applied":[96],"tipping":[99,157],"point":[100],"discovery.":[101],"The":[102],"NS-QAPT":[103],"method":[104,143],"bidirectional":[107],"encoder-decoder":[108],"architecture":[109],"that":[110],"translates":[111],"between":[112,128],"domain-specific":[113,147],"questions":[114],"executable":[116,151],"programs":[117,152],"used":[118],"direct":[120],"the":[121,159,162],"acting":[124],"bridge":[127],"scientists":[130],"models.":[134],"We":[135],"show":[136],"early":[137],"compelling":[138],"translation":[142],"introduce":[145],"language":[148],"associated":[150],"commonly":[155],"known":[156],"point,":[158],"collapse":[160],"Atlantic":[163],"Meridional":[164],"Overturning":[165],"Circulation":[166],"(AMOC).":[167]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4381573093","counts_by_year":[],"updated_date":"2025-01-06T06:25:46.020473","created_date":"2023-06-22"}