{"id":"https://openalex.org/W7124277684","doi":"https://doi.org/10.48550/arxiv.2601.08999","title":"Physics-Guided Counterfactual Explanations for Large-Scale Multivariate Time Series: Application in Scalable and Interpretable SEP Event Prediction","display_name":"Physics-Guided Counterfactual Explanations for Large-Scale Multivariate Time Series: Application in Scalable and Interpretable SEP Event Prediction","publication_year":2026,"publication_date":"2026-01-13","ids":{"openalex":"https://openalex.org/W7124277684","doi":"https://doi.org/10.48550/arxiv.2601.08999"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2601.08999","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.08999","pdf_url":"https://arxiv.org/pdf/2601.08999","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":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2601.08999","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053911422","display_name":"Pranjal Patil","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patil, Pranjal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018886706","display_name":"Anli Ji","orcid":"https://orcid.org/0000-0002-1551-2370","observed_orcids":["https://orcid.org/0000-0002-1551-2370"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Anli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043887593","display_name":"Berkay Aydin","orcid":"https://orcid.org/0000-0002-9799-9265","observed_orcids":["https://orcid.org/0000-0002-9799-9265"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aydin, Berkay","raw_affiliation_strings":[],"raw_orcid":null,"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":0,"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/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/T10251","display_name":"Solar and Space Plasma Dynamics","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-explanations","display_name":"counterfactual explanations","score":0.9480000138282776},{"id":"https://openalex.org/keywords/solar-energetic-particle-events","display_name":"solar energetic particle events","score":0.9399999976158142},{"id":"https://openalex.org/keywords/multivariate-time-series-classification","display_name":"multivariate time series classification","score":0.9100000262260437},{"id":"https://openalex.org/keywords/space-weather","display_name":"space weather","score":0.5120000243186951},{"id":"https://openalex.org/keywords/model-interpretability","display_name":"model interpretability","score":0.8339999914169312},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"dynamic time warping","score":0.7360000014305115}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9498000144958496},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6686999797821045},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.5903000235557556},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5812000036239624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5055999755859375},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.4507000148296356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4390000104904175},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38580000400543213},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.3822000026702881},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C16405173","wikidata":"https://www.wikidata.org/wiki/Q192316","display_name":"Geostationary orbit","level":3,"score":0.3684000074863434},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36000001430511475},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2601.08999","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.08999","pdf_url":"https://arxiv.org/pdf/2601.08999","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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2601.08999","doi":"https://doi.org/10.48550/arxiv.2601.08999","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.08999","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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2601.08999","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.08999","pdf_url":"https://arxiv.org/pdf/2601.08999","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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7134963276","https://openalex.org/W4403251379","https://openalex.org/W4360764280","https://openalex.org/W4392539492","https://openalex.org/W4391448591","https://openalex.org/W4396615939","https://openalex.org/W4407259711","https://openalex.org/W7151030287","https://openalex.org/W6898645626","https://openalex.org/W4292945934"],"abstract_inverted_index":{"Accurate":[0],"prediction":[1],"of":[2,23],"solar":[3,108],"energetic":[4,109],"particle":[5],"events":[6],"is":[7],"vital":[8],"for":[9,68,90,183],"safeguarding":[10],"satellites,":[11],"astronauts,":[12],"and":[13,134,160,176],"space-based":[14],"infrastructure.":[15],"Modern":[16],"space":[17],"weather":[18],"monitoring":[19],"generates":[20,169],"massive":[21],"volumes":[22],"high-frequency,":[24],"multivariate":[25],"time":[26,95],"series":[27,96],"(MVTS)":[28],"data":[29,47,189],"from":[30],"sources":[31],"such":[32,144],"as":[33,64,145],"the":[34,126,167,181],"Geostationary":[35],"perational":[36],"Environmental":[37],"Satellites":[38],"(GOES).":[39],"Machine":[40],"learning":[41],"(ML)":[42],"models":[43],"trained":[44],"on":[45],"this":[46,113,150],"show":[48],"strong":[49],"predictive":[50],"power,":[51],"but":[52],"most":[53],"existing":[54,73],"methods":[55],"overlook":[56],"domain-specific":[57],"feasibility":[58],"constraints.":[59],"Counterfactual":[60,84],"explanations":[61,93,130,156,171],"have":[62],"emerged":[63],"a":[65,82,87],"key":[66],"tool":[67],"improving":[69],"model":[70],"interpretability,":[71],"yet":[72],"approaches":[74],"rarely":[75],"enforce":[76],"physical":[77,104],"plausibility.":[78],"This":[79],"work":[80],"introduces":[81],"Physics-Guided":[83],"Explanation":[85],"framework,":[86],"novel":[88],"method":[89],"generating":[91],"counterfactual":[92,129,155,170,185],"in":[94,119,162,187],"classification":[97],"tasks":[98],"that":[99,153,172],"remain":[100],"consistent":[101],"with":[102,131],"underlying":[103],"principles.":[105],"Applied":[106],"to":[107,141],"particles":[110],"(SEP)":[111],"forecasting,":[112],"framework":[114,151,168],"achieves":[115],"over":[116],"80%":[117],"reduction":[118],"Dynamic":[120],"Time":[121],"Warping":[122],"(DTW)":[123],"distance":[124],"increasing":[125],"proximity,":[127],"produces":[128],"higher":[132],"sparsity,":[133],"reduces":[135],"runtime":[136],"by":[137],"nearly":[138],"50%":[139],"compared":[140],"state-of-the-art":[142],"baselines":[143],"DiCE.":[146],"Beyond":[147],"numerical":[148],"improvements,":[149],"ensures":[152],"generated":[154],"are":[157,173],"physically":[158,177],"plausible":[159],"actionable":[161],"scientific":[163],"domains.":[164],"In":[165],"summary,":[166],"both":[174],"valid":[175],"consistent,":[178],"while":[179],"laying":[180],"foundation":[182],"scalable":[184],"generation":[186],"big":[188],"environments.":[190]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-01-16T00:00:00"}