{"id":"https://openalex.org/W4388209654","doi":"https://doi.org/10.1088/2632-2153/ad0938","title":"Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data","display_name":"Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data","publication_year":2023,"publication_date":"2023-11-02","ids":{"openalex":"https://openalex.org/W4388209654","doi":"https://doi.org/10.1088/2632-2153/ad0938"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/ad0938","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad0938","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad0938/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad0938/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053375156","display_name":"S. J. Jadhav","orcid":"https://orcid.org/0000-0003-0554-0084"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Shreejit Jadhav","raw_affiliation_strings":["Centre for Astrophysics and Supercomputing, Swinburne University of Technology, John Street, Hawthorn, Melbourne, Victoria, 3122, AUSTRALIA"],"raw_orcid":"https://orcid.org/0000-0003-0554-0084","affiliations":[{"raw_affiliation_string":"Centre for Astrophysics and Supercomputing, Swinburne University of Technology, John Street, Hawthorn, Melbourne, Victoria, 3122, AUSTRALIA","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103276544","display_name":"Mihir Shrivastava","orcid":"https://orcid.org/0000-0002-6767-139X"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mihir Shrivastava","raw_affiliation_strings":["Indian Institute of Technology Kharagpur, Kharagpur, Kharagpur, West Bengal, 721302, INDIA"],"raw_orcid":"https://orcid.org/0000-0002-6767-139X","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Kharagpur, Kharagpur, Kharagpur, West Bengal, 721302, INDIA","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114376152","display_name":"S. Mitra","orcid":"https://orcid.org/0000-0002-0800-4626"},"institutions":[{"id":"https://openalex.org/I59781447","display_name":"Inter-University Centre for Astronomy and Astrophysics","ror":"https://ror.org/04etcj997","country_code":"IN","type":"facility","lineage":["https://openalex.org/I59781447"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanjit Mitra","raw_affiliation_strings":["Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune, Maharashtra, 411007, INDIA"],"raw_orcid":"https://orcid.org/0000-0002-0800-4626","affiliations":[{"raw_affiliation_string":"Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune, Maharashtra, 411007, INDIA","institution_ids":["https://openalex.org/I59781447"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053375156"],"corresponding_institution_ids":["https://openalex.org/I57093077"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":1.8913,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8539977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"4","issue":"4","first_page":"045028","last_page":"045028"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10463","display_name":"Pulsars and Gravitational Waves Research","score":0.9980000257492065,"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/T10463","display_name":"Pulsars and Gravitational Waves Research","score":0.9980000257492065,"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/T11323","display_name":"Gamma-ray bursts and supernovae","score":0.9803000092506409,"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/robustness","display_name":"Robustness (evolution)","score":0.6834560036659241},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6796591281890869},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6019916534423828},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5495268106460571},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.47319504618644714},{"id":"https://openalex.org/keywords/ligo","display_name":"LIGO","score":0.45056313276290894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43821483850479126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40438708662986755},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4033350348472595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37658485770225525},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2767913341522217},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.25759345293045044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1540220081806183}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6834560036659241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796591281890869},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6019916534423828},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5495268106460571},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.47319504618644714},{"id":"https://openalex.org/C2780688901","wikidata":"https://www.wikidata.org/wiki/Q255371","display_name":"LIGO","level":3,"score":0.45056313276290894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43821483850479126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40438708662986755},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4033350348472595},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37658485770225525},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2767913341522217},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.25759345293045044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1540220081806183},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1088/2632-2153/ad0938","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad0938","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad0938/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e5c42ebe72974a3b99c58d89f52196fe","is_oa":true,"landing_page_url":"https://doaj.org/article/e5c42ebe72974a3b99c58d89f52196fe","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 4, Iss 4, p 045028 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/ad0938","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad0938","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad0938/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1776145124","display_name":null,"funder_award_id":"DST/SJF/PSA-02/2015-16","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320320721","display_name":"Council of Scientific and Industrial Research, India","ror":"https://ror.org/021wm7p51"},{"id":"https://openalex.org/F4320325255","display_name":"Ministry of Electronics and Information technology","ror":null},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"},{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388209654.pdf"},"referenced_works_count":100,"referenced_works":["https://openalex.org/W1631642545","https://openalex.org/W1749804791","https://openalex.org/W1777070175","https://openalex.org/W1932198206","https://openalex.org/W1994870116","https://openalex.org/W2051449498","https://openalex.org/W2070717869","https://openalex.org/W2115305599","https://openalex.org/W2116209992","https://openalex.org/W2183341477","https://openalex.org/W2252795400","https://openalex.org/W2273772273","https://openalex.org/W2293872166","https://openalex.org/W2423333910","https://openalex.org/W2437571239","https://openalex.org/W2523600896","https://openalex.org/W2526275824","https://openalex.org/W2568927912","https://openalex.org/W2581294054","https://openalex.org/W2621266390","https://openalex.org/W2753877653","https://openalex.org/W2756512191","https://openalex.org/W2758785873","https://openalex.org/W2765081049","https://openalex.org/W2765424254","https://openalex.org/W2767526854","https://openalex.org/W2768286292","https://openalex.org/W2775923832","https://openalex.org/W2790235314","https://openalex.org/W2809820731","https://openalex.org/W2899039106","https://openalex.org/W2939997667","https://openalex.org/W2940261095","https://openalex.org/W2944526934","https://openalex.org/W2951526967","https://openalex.org/W2953142974","https://openalex.org/W2963246377","https://openalex.org/W2971836485","https://openalex.org/W2973034339","https://openalex.org/W2975828310","https://openalex.org/W2979653407","https://openalex.org/W2995259291","https://openalex.org/W2996189182","https://openalex.org/W2996762233","https://openalex.org/W2999365684","https://openalex.org/W3004476046","https://openalex.org/W3006452559","https://openalex.org/W3007030816","https://openalex.org/W3017872349","https://openalex.org/W3025130744","https://openalex.org/W3036761016","https://openalex.org/W3040417103","https://openalex.org/W3042625762","https://openalex.org/W3043653413","https://openalex.org/W3043907802","https://openalex.org/W3062583422","https://openalex.org/W3081939279","https://openalex.org/W3093187712","https://openalex.org/W3094812309","https://openalex.org/W3098672780","https://openalex.org/W3100262809","https://openalex.org/W3100399574","https://openalex.org/W3102552189","https://openalex.org/W3102883102","https://openalex.org/W3102981061","https://openalex.org/W3103557498","https://openalex.org/W3103749085","https://openalex.org/W3105546891","https://openalex.org/W3115719931","https://openalex.org/W3123782013","https://openalex.org/W3134781796","https://openalex.org/W3139116291","https://openalex.org/W3154616697","https://openalex.org/W3163746392","https://openalex.org/W3173423506","https://openalex.org/W3173762688","https://openalex.org/W3175446831","https://openalex.org/W3190756216","https://openalex.org/W3194128951","https://openalex.org/W3215517674","https://openalex.org/W3217440745","https://openalex.org/W4220925139","https://openalex.org/W4221020852","https://openalex.org/W4221161524","https://openalex.org/W4225457842","https://openalex.org/W4225458823","https://openalex.org/W4234856688","https://openalex.org/W4281493154","https://openalex.org/W4290728118","https://openalex.org/W4298289240","https://openalex.org/W4308709987","https://openalex.org/W4320002409","https://openalex.org/W4376143837","https://openalex.org/W4380632548","https://openalex.org/W6637568146","https://openalex.org/W6640300313","https://openalex.org/W6729210268","https://openalex.org/W6780819241","https://openalex.org/W6782396100","https://openalex.org/W6849469826"],"related_works":["https://openalex.org/W4383604425","https://openalex.org/W3100169557","https://openalex.org/W3171538263","https://openalex.org/W2598128268","https://openalex.org/W2035798170","https://openalex.org/W2732011120","https://openalex.org/W1655247885","https://openalex.org/W2560323587","https://openalex.org/W2728580611","https://openalex.org/W2615272281"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"ability":[2],"of":[3,32,44,78,92,133,141,186,196,247,273],"deep":[4],"learning":[5],"(DL)":[6],"approaches":[7],"to":[8,115,191,208],"learn":[9],"generalised":[10],"signal":[11,95],"and":[12,37,61,67,221,255,291],"noise":[13],"models,":[14],"coupled":[15],"with":[16],"their":[17,49],"fast":[18],"inference":[19],"on":[20,125,250,263],"GPUs,":[21],"holds":[22],"great":[23],"promise":[24],"for":[25,117],"enhancing":[26],"gravitational-wave":[27],"(GW)":[28],"searches":[29],"in":[30,74,97,173,224,245],"terms":[31,246],"speed,":[33],"parameter":[34],"space":[35],"coverage,":[36],"search":[38,116,262,297],"sensitivity.":[39],"However,":[40,136],"the":[41,72,76,89,93,98,134,139,142,171,184,188,193,200,225,232,296],"opaque":[42],"nature":[43],"DL":[45,58],"models":[46,156],"severely":[47],"harms":[48],"reliability.":[50,68],"In":[51],"this":[52],"work,":[53],"we":[54,70,111,169,210,276],"meticulously":[55],"develop":[56],"a":[57,83,101,107,113,163,174,178,260],"model":[59,143,172,189,248],"stage-wise":[60],"work":[62],"towards":[63,166],"improving":[64],"its":[65,147],"robustness":[66,140,204],"First,":[69],"address":[71],"problems":[73],"maintaining":[75],"purity":[77],"training":[79],"data":[80,128,253],"by":[81,199],"deriving":[82],"new":[84],"metric":[85],"that":[86,236],"better":[87],"reflects":[88],"visual":[90],"strength":[91],"\u2018chirp\u2019":[94],"features":[96,227],"data.":[99],"Using":[100],"reduced,":[102],"smooth":[103],"representation":[104],"obtained":[105,299],"through":[106,144,216],"variational":[108],"auto-encoder":[109],"(VAE),":[110],"build":[112],"classifier":[114],"compact":[118],"binary":[119],"coalescence":[120],"(CBC)":[121],"signals.":[122],"Our":[123],"tests":[124],"real":[126,251],"LIGO":[127,252,274],"show":[129,235],"an":[130,301],"impressive":[131],"performance":[132,249],"model.":[135,233],"upon":[137],"probing":[138],"adversarial":[145,180],"attacks,":[146],"simple":[148],"failure":[149,197],"modes":[150,195],"were":[151],"identified,":[152],"underlining":[153],"how":[154],"such":[155,217],"can":[157],"still":[158],"be":[159],"highly":[160],"fragile.":[161],"As":[162],"first":[164],"step":[165],"bringing":[167],"robustness,":[168],"retrain":[170],"novel":[175],"framework":[176],"involving":[177],"generative":[179],"network":[181],"(GAN).":[182],"Over":[183],"course":[185],"training,":[187,218],"learns":[190],"eliminate":[192],"primary":[194],"identified":[198],"adversaries.":[201],"Although":[202],"absolute":[203],"is":[205],"practically":[206,242],"impossible":[207],"achieve,":[209],"demonstrate":[211],"some":[212],"fundamental":[213],"improvements":[214],"earned":[215],"like":[219],"sparseness":[220],"reduced":[222],"degeneracy":[223],"extracted":[226],"at":[228,241],"different":[229],"layers":[230],"inside":[231],"We":[234,293],"these":[237],"gains":[238],"are":[239],"achieved":[240],"zero":[243],"loss":[244],"before":[254],"after":[256],"GAN":[257],"training.":[258],"Through":[259],"direct":[261],"<mml:math":[264],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[265],"overflow=\"scroll\">":[266],"<mml:mrow>":[267],"<mml:mo>\u223c</mml:mo>":[268],"</mml:mrow>":[269],"<mml:mn>8.8</mml:mn>":[270],"</mml:math>":[271],"days":[272],"data,":[275],"recover":[277],"two":[278],"significant":[279],"CBC":[280],"events":[281],"from":[282,300],"GWTC-2.1":[283],"(Abbott":[284],"et":[285],"al":[286],"2022":[287],"2108.01045":[288],"[gr-qc]),":[289],"GW190519_153544":[290],"GW190521_074359.":[292],"also":[294],"report":[295],"sensitivity":[298],"injection":[302],"study.":[303]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}