{"id":"https://openalex.org/W4392931647","doi":"https://doi.org/10.1109/icassp48485.2024.10447192","title":"SPASE: Spatial Saliency Explanation For Time Series Models","display_name":"SPASE: Spatial Saliency Explanation For Time Series Models","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392931647","doi":"https://doi.org/10.1109/icassp48485.2024.10447192"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10447192","doi":"https://doi.org/10.1109/icassp48485.2024.10447192","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10447192","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-3290148/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045547703","display_name":"Pranay Lohia","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pranay Lohia","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035714586","display_name":"Badri N. Patro","orcid":"https://orcid.org/0000-0002-2585-7014","observed_orcids":["https://orcid.org/0000-0002-2585-7014"]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Badri Narayana Patro","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041018414","display_name":"Naveen Panwar","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naveen Panwar","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055130710","display_name":"Vijay Srinivas Agneeswaran","orcid":"https://orcid.org/0009-0009-9891-7645","observed_orcids":["https://orcid.org/0009-0009-9891-7645"]},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vijay Agneeswaran","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":0.1579,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3468056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"5180","last_page":"5184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":1.0,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10799","display_name":"Data Visualization and Analytics","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/model-explainability","display_name":"model explainability","score":0.7549999952316284},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.7390000224113464},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.9449999928474426},{"id":"https://openalex.org/keywords/time-series-anomaly-detection","display_name":"time series anomaly detection","score":0.8600000143051147},{"id":"https://openalex.org/keywords/black-box-modeling","display_name":"black-box models","score":0.8569999933242798},{"id":"https://openalex.org/keywords/spatial-saliency","display_name":"spatial saliency","score":0.8859999775886536},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.5529999732971191},{"id":"https://openalex.org/keywords/spase","display_name":"SPASE","score":0.5429999828338623}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9487792253494263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7316824793815613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170650959014893},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6575908064842224},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.656173050403595},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5811508297920227},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5461401343345642},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.530487596988678},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5289573669433594},{"id":"https://openalex.org/C180932941","wikidata":"https://www.wikidata.org/wiki/Q997233","display_name":"White box","level":2,"score":0.4994492530822754},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp48485.2024.10447192","doi":"https://doi.org/10.1109/icassp48485.2024.10447192","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp48485.2024.10447192","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"doi:10.21203/rs.3.rs-3290148/v1","doi":"https://doi.org/10.21203/rs.3.rs-3290148/v1","is_oa":true,"landing_page_url":"http://dx.doi.org/10.21203/rs.3.rs-3290148/v1","pdf_url":"https://www.researchsquare.com/article/rs-3290148/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-3290148/v1","doi":"https://doi.org/10.21203/rs.3.rs-3290148/v1","is_oa":true,"landing_page_url":"http://dx.doi.org/10.21203/rs.3.rs-3290148/v1","pdf_url":"https://www.researchsquare.com/article/rs-3290148/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392931647.pdf","grobid_xml":"https://content.openalex.org/works/W4392931647.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W2295107390","https://openalex.org/W2516809705","https://openalex.org/W2594633041","https://openalex.org/W2605409611","https://openalex.org/W2616247523","https://openalex.org/W2618851150","https://openalex.org/W2765793020","https://openalex.org/W2962858109","https://openalex.org/W3000346474","https://openalex.org/W3120740533","https://openalex.org/W3150957536","https://openalex.org/W3154413838","https://openalex.org/W4296437236","https://openalex.org/W6907814131"],"related_works":["https://openalex.org/W4386224394","https://openalex.org/W7124457873","https://openalex.org/W6989198916","https://openalex.org/W7131373100","https://openalex.org/W4360832008","https://openalex.org/W3154413838","https://openalex.org/W3043681824","https://openalex.org/W7089764424","https://openalex.org/W4318070633","https://openalex.org/W4400439043"],"abstract_inverted_index":{"Abstract":[0],"We":[1,137],"have":[2,40],"seen":[3],"recent":[4],"advances":[5],"in":[6,29,47,68,92],"the":[7,21,42,45,66,93],"field":[8],"of":[9,31,44,50,95,141],"Machine":[10],"Learning":[11,14],"(ML),":[12],"Deep":[13],"(DL),":[15],"and":[16,27,33,60,73,101,113,133,144],"Artificial":[17],"intelligence":[18],"(AI)":[19],"that":[20],"models":[22,39],"are":[23],"becoming":[24],"increasingly":[25],"complex":[26,37],"large":[28],"terms":[30],"architecture":[32],"parameter":[34],"size.":[35],"These":[36],"ML/DL":[38],"beaten":[41],"state":[43],"art":[46],"most":[48],"fields":[49],"computer":[51,54],"science":[52],"like":[53],"vision,":[55],"NLP,":[56],"tabular":[57],"data":[58],"prediction":[59],"time":[61,122,129],"series":[62,123,130],"forecasting,":[63],"etc.":[64],"With":[65],"increase":[67],"models\u2019":[69],"performance,":[70],"model":[71,80,96,131],"explainability":[72,97,124],"interpretability":[74],"has":[75,88],"become":[76],"essential":[77],"to":[78],"explain/justify":[79],"outcome,":[81],"especially":[82],"for":[83,98,110,127],"business":[84],"use":[85],"cases.":[86],"There":[87],"been":[89],"significant":[90],"improvement":[91],"domain":[94],"Computer":[99],"Vision":[100],"Natural":[102],"Language":[103],"Processing":[104],"(NLP)":[105],"tasks":[106],"with":[107],"fundamental":[108],"research":[109],"both":[111],"black-box":[112,128],"white-box":[114],"techniques.":[115],"In":[116],"this":[117],"paper,":[118],"we":[119],"proposed":[120],"novel":[121],"techniques":[125],"SPASE":[126],"forecasting":[132],"anomaly":[134],"detection":[135],"problems.":[136],"also":[138],"outline":[139],"details":[140],"its":[142],"implementation":[143],"integration":[145],"into":[146],"Microsoft":[147],"Azure":[148],"products.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2024-03-19T00:00:00"}