{"id":"https://openalex.org/W7131377600","doi":"https://doi.org/10.1109/icdm65498.2025.00161","title":"On the Necessity of Multi-Domain Explanation: An Uncertainty Principle Approach for Deep Time Series Models","display_name":"On the Necessity of Multi-Domain Explanation: An Uncertainty Principle Approach for Deep Time Series Models","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7131377600","doi":"https://doi.org/10.1109/icdm65498.2025.00161"},"language":null,"primary_location":{"id":"doi:10.1109/icdm65498.2025.00161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm65498.2025.00161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048444456","display_name":"Shahbaz Rezaei","orcid":"https://orcid.org/0000-0003-1583-0114"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shahbaz Rezaei","raw_affiliation_strings":["University of California,Davis,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Davis,CA,USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048314614","display_name":"Avishai Halev","orcid":"https://orcid.org/0009-0004-4348-5447"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avishai Halev","raw_affiliation_strings":["University of California,Davis,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Davis,CA,USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126850482","display_name":"Xin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["University of California,Davis,CA,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Davis,CA,USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048444456"],"corresponding_institution_ids":["https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.77189991,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1515","last_page":"1524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.1800999939441681,"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"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.1800999939441681,"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"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.16920000314712524,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.12839999794960022,"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":[{"id":"https://openalex.org/keywords/attribution","display_name":"Attribution","score":0.6057000160217285},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5460000038146973},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5037000179290771},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.48989999294281006},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4754999876022339},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.4634000062942505}],"concepts":[{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.6057000160217285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5792999863624573},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5460000038146973},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5037000179290771},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.48989999294281006},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4754999876022339},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4634000062942505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4099999964237213},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32440000772476196},{"id":"https://openalex.org/C127934551","wikidata":"https://www.wikidata.org/wiki/Q1148098","display_name":"Harmonic","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2989000082015991},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C181543814","wikidata":"https://www.wikidata.org/wiki/Q44746","display_name":"Uncertainty principle","level":3,"score":0.27649998664855957}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm65498.2025.00161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm65498.2025.00161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.4747958779335022}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1480912861","https://openalex.org/W1849277567","https://openalex.org/W1969589212","https://openalex.org/W1975601543","https://openalex.org/W2015064056","https://openalex.org/W2090099030","https://openalex.org/W2094654291","https://openalex.org/W2125455772","https://openalex.org/W2173401535","https://openalex.org/W2516809705","https://openalex.org/W2972810968","https://openalex.org/W2988244882","https://openalex.org/W3005245032","https://openalex.org/W3120617215","https://openalex.org/W3125923948","https://openalex.org/W3188872815","https://openalex.org/W4318828813","https://openalex.org/W4391486587","https://openalex.org/W4413192228"],"related_works":[],"abstract_inverted_index":{"A":[0,16],"prevailing":[1,55],"approach":[2,56,243],"to":[3,9,58,120,160,233],"explain":[4],"time":[5,13,20,35,65,98,182,196,219],"series":[6,21],"models":[7],"is":[8,23,57,74,298],"generate":[10,89],"attribution":[11,73],"in":[12,19,33,45,63,68,83,96,148,154,179,194],"domain":[14,36,66,70,222],"input.":[15],"recent":[17],"development":[18],"XAI":[22,43,60,86,162,249,270],"the":[24,34,64,69,72,97,129,142,161,181,195,218,234,239,273,286],"concept":[25],"of":[26,107,131,241,255,263,275],"explanation":[27],"spaces,":[28],"where":[29,71],"any":[30,41],"model":[31],"trained":[32],"can":[37,88,175],"be":[38,118,176,230],"interpreted":[39],"with":[40],"existing":[42,276],"method":[44],"alternative":[46],"domains,":[47],"such":[48,137],"as":[49,291],"frequency":[50,100,184,198,221],"or":[51,67],"time-frequency":[52],"domain.":[53],"The":[54,260,295],"present":[59],"attributions":[61,90,116,193],"either":[62],"most":[75],"sparse.":[76],"In":[77,209],"this":[78,188,201,242],"paper,":[79],"we":[80,140,190],"demonstrate":[81],"that":[82,91,102,113,204,217,278],"certain":[84],"cases,":[85],"methods":[87,271],"highlight":[92],"fundamentally":[93],"different":[94],"features":[95],"and":[99,151,157,183,197,220,251,257,269],"domains":[101,199],"are":[103],"not":[104,225],"direct":[105],"counterparts":[106],"one":[108],"another.":[109],"This":[110,164,284],"observation":[111],"suggests":[112],"both":[114,180,231],"domains'":[115],"should":[117,229],"presented":[119,232],"achieve":[121],"a":[122,167,173,214,252,292],"more":[123],"comprehensive":[124],"interpretation.":[125],"Thus":[126],"it":[127],"shows":[128],"necessity":[130],"multi-domain":[132,289],"explanation.":[133],"To":[134],"quantify":[135],"when":[136],"cases":[138],"arise,":[139],"introduce":[141],"uncertainty":[143],"principle":[144,165],"(UP),":[145],"originally":[146],"developed":[147],"quantum":[149],"mechanics":[150],"later":[152],"studied":[153],"harmonic":[155],"analysis":[156],"signal":[158,174],"processing,":[159],"literature.":[163],"establishes":[166],"lower":[168],"bound":[169],"on":[170,281],"how":[171],"much":[172],"simultaneously":[177],"localized":[178],"domains.":[185],"By":[186],"leveraging":[187],"concept,":[189],"assess":[191],"whether":[192],"violate":[200],"bound,":[202],"indicating":[203],"they":[205],"emphasize":[206],"distinct":[207],"features.":[208],"other":[210],"words,":[211],"UP":[212,264],"provides":[213],"sufficient":[215],"condition":[216],"explanations":[223,290],"do":[224],"match":[226],"and,":[227],"hence,":[228],"end":[235],"user.":[236],"We":[237],"validate":[238],"effectiveness":[240],"across":[244,266],"various":[245,267],"deep":[246],"learning":[247],"models,":[248],"methods,":[250],"wide":[253],"range":[254],"classification":[256],"forecasting":[258],"datasets.":[259],"frequent":[261],"occurrence":[262],"violations":[265],"datasets":[268],"highlights":[272],"limitations":[274],"approaches":[277],"focus":[279],"solely":[280],"time-domain":[282],"explanations.":[283],"underscores":[285],"need":[287],"for":[288],"new":[293],"paradigm.":[294],"source":[296],"code":[297],"available":[299],"at":[300],"https://github.com/shrezaei/TS-X-spaces":[301]},"counts_by_year":[],"updated_date":"2026-02-27T06:17:20.405678","created_date":"2026-02-26T00:00:00"}
