{"id":"https://openalex.org/W7106715671","doi":"https://doi.org/10.48550/arxiv.2511.18477","title":"A Deep Multimodal Multi--Head Neural Network for Joint Estimation of Stellar Age, Lifetime, and Evolutionary Stage","display_name":"A Deep Multimodal Multi--Head Neural Network for Joint Estimation of Stellar Age, Lifetime, and Evolutionary Stage","publication_year":2025,"publication_date":"2025-11-23","ids":{"openalex":"https://openalex.org/W7106715671","doi":"https://doi.org/10.48550/arxiv.2511.18477"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2511.18477","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.18477","pdf_url":"https://arxiv.org/pdf/2511.18477","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2511.18477","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Puah, Jing Rou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210110072","display_name":"Raffles University Iskandar","ror":"https://ror.org/02nd88213","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210110072"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Puah, Jing Rou","raw_affiliation_strings":["Faculty of AI & Robotics, Raffles University, Johor Bahru, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of AI & Robotics, Raffles University, Johor Bahru, Malaysia","institution_ids":["https://openalex.org/I4210110072"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108007139","display_name":"Sa\u0161a Arsovski","orcid":"https://orcid.org/0000-0001-5981-9473","observed_orcids":["https://orcid.org/0000-0001-5981-9473"]},"institutions":[{"id":"https://openalex.org/I4210110072","display_name":"Raffles University Iskandar","ror":"https://ror.org/02nd88213","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210110072"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Arsovski, Sasa","raw_affiliation_strings":["Faculty of AI & Robotics, Raffles University, Johor Bahru, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of AI & Robotics, Raffles University, Johor Bahru, Malaysia","institution_ids":["https://openalex.org/I4210110072"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210110072"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"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/T10039","display_name":"Stellar, planetary, and galactic studies","score":0.9945999979972839,"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"}},"topics":[{"id":"https://openalex.org/T10039","display_name":"Stellar, planetary, and galactic studies","score":0.9945999979972839,"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/T12917","display_name":"Astronomy and Astrophysical Research","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"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/T14163","display_name":"Astronomical Observations and Instrumentation","score":0.0010999999940395355,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stellar-age-estimation","display_name":"stellar age estimation","score":0.9729999899864197},{"id":"https://openalex.org/keywords/stellar-lifetimes","display_name":"stellar lifetimes","score":0.9100000262260437},{"id":"https://openalex.org/keywords/stellar-evolutionary-stage","display_name":"stellar evolutionary stage","score":0.9520000219345093},{"id":"https://openalex.org/keywords/stellar-parameter-estimation","display_name":"stellar parameter estimation","score":0.8479999899864197},{"id":"https://openalex.org/keywords/multimodal-fusion","display_name":"multimodal fusion","score":0.6840000152587891},{"id":"https://openalex.org/keywords/spectroscopic-data","display_name":"spectral data","score":0.7820000052452087},{"id":"https://openalex.org/keywords/photometric-data","display_name":"photometric data","score":0.984000027179718},{"id":"https://openalex.org/keywords/vision-transformer","display_name":"vision transformer","score":0.5490000247955322},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7919999957084656},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"multi-task learning","score":0.859000027179718},{"id":"https://openalex.org/keywords/uncertainty-calibration","display_name":"uncertainty calibration","score":0.7440000176429749},{"id":"https://openalex.org/keywords/monte-carlo-dropout","display_name":"Monte Carlo dropout","score":0.7739999890327454}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6977999806404114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6553000211715698},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6201000213623047},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.612500011920929},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5508000254631042},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47589999437332153},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.45190000534057617},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38040000200271606},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3603000044822693},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.3296000063419342},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2791000008583069},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C137583809","wikidata":"https://www.wikidata.org/wiki/Q1096404","display_name":"Modern evolutionary synthesis","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2511.18477","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.18477","pdf_url":"https://arxiv.org/pdf/2511.18477","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2511.18477","doi":"https://doi.org/10.48550/arxiv.2511.18477","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.18477","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2511.18477","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.18477","pdf_url":"https://arxiv.org/pdf/2511.18477","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7106715671.pdf","grobid_xml":"https://content.openalex.org/works/W7106715671.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2798812533","https://openalex.org/W2908510526","https://openalex.org/W6947961063"],"related_works":["https://openalex.org/W4416402668","https://openalex.org/W4414064245","https://openalex.org/W3170266457","https://openalex.org/W4410140446","https://openalex.org/W7164836202","https://openalex.org/W7136326972","https://openalex.org/W7133657097","https://openalex.org/W7106587659","https://openalex.org/W7171394255","https://openalex.org/W7159546778"],"abstract_inverted_index":{"Accurate":[0],"estimation":[1],"of":[2],"stellar":[3,6,144],"parameters":[4],"--":[5,12],"age,":[7,58],"lifetime,":[8,59],"and":[9,29,44,60,94,103,124,137],"evolutionary":[10,61,73],"stage":[11,62,74],"remains":[13],"a":[14,21,38,45,48,115,139],"fundamental":[15],"challenge":[16],"in":[17,122],"astrophysics.":[18],"We":[19,85],"introduce":[20],"hybrid":[22],"deep":[23],"learning":[24],"architecture":[25],"combining":[26],"multimodal":[27,143],"spectroscopic":[28],"photometric":[30],"data":[31,95],"from":[32,68],"SDSS":[33],"DR17.":[34],"The":[35,111],"model":[36,92,113],"comprises":[37],"Multi-Layer":[39],"Perceptron":[40],"for":[41,51,57,142],"numerical":[42],"features":[43],"CNN":[46],"with":[47,53,72],"Vision":[49],"Transformer":[50],"spectra,":[52],"three":[54],"output":[55],"heads":[56],"prediction.":[63],"Training":[64],"labels":[65],"are":[66],"derived":[67],"MIST":[69],"v1.2":[70],"isochrones,":[71],"binned":[75],"into":[76],"five":[77],"classes":[78],"(Hot,":[79],"Medium,":[80],"Cool,":[81],"Subgiant,":[82],"Red":[83],"Giant).":[84],"conduct":[86],"multi-phase":[87],"evaluation:":[88],"Phase":[89,98,104],"I":[90],"explores":[91],"architectures":[93],"balancing":[96],"strategies,":[97],"II":[99],"tunes":[100],"architectural":[101],"complexity,":[102],"III":[105],"optimizes":[106],"the":[107],"multi-task":[108],"loss":[109],"composition.":[110],"final":[112],"achieves":[114],"balance":[116],"between":[117],"precision":[118],"(Age":[119],"RMSE":[120],"0.093":[121],"$\\log(\\mathrm{yrs})$)":[123],"physical":[125],"realism.":[126],"Monte":[127],"Carlo":[128],"Dropout":[129],"confirms":[130],"well-calibrated":[131],"uncertainties,":[132],"enabling":[133],"meaningful":[134],"astrophysical":[135],"interpretation":[136],"establishing":[138],"new":[140],"benchmark":[141],"parameter":[145],"estimation.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2025-11-27T00:00:00"}
