{"id":"https://openalex.org/W4402010817","doi":"https://doi.org/10.1007/s11222-024-10486-6","title":"SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences","display_name":"SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences","publication_year":2024,"publication_date":"2024-08-29","ids":{"openalex":"https://openalex.org/W4402010817","doi":"https://doi.org/10.1007/s11222-024-10486-6"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-024-10486-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-024-10486-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-024-10486-6.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-024-10486-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005475714","display_name":"Samuel Stockman","orcid":"https://orcid.org/0000-0003-1553-9618"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Samuel Stockman","raw_affiliation_strings":["School of Mathematics, University of Bristol, Woodland Rd, Bristol, BS8 1UG, UK"],"affiliations":[{"raw_affiliation_string":"School of Mathematics, University of Bristol, Woodland Rd, Bristol, BS8 1UG, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027125275","display_name":"Daniel J. Lawson","orcid":"https://orcid.org/0000-0002-5311-6213"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Daniel J. Lawson","raw_affiliation_strings":["School of Mathematics, University of Bristol, Woodland Rd, Bristol, BS8 1UG, UK"],"affiliations":[{"raw_affiliation_string":"School of Mathematics, University of Bristol, Woodland Rd, Bristol, BS8 1UG, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008506653","display_name":"Maximilian J. Werner","orcid":"https://orcid.org/0000-0002-2430-2631"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maximilian J. Werner","raw_affiliation_strings":["School of Earth Sciences, University of Bristol, Wills Memorial Building, Bristol, BS8 1RL, UK"],"affiliations":[{"raw_affiliation_string":"School of Earth Sciences, University of Bristol, Wills Memorial Building, Bristol, BS8 1RL, UK","institution_ids":["https://openalex.org/I36234482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5005475714"],"corresponding_institution_ids":["https://openalex.org/I36234482"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":0.536,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65192839,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"34","issue":"5","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10110","display_name":"earthquake and tectonic studies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10110","display_name":"earthquake and tectonic studies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9890000224113464,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.9745000004768372,"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/algorithm","display_name":"Algorithm","score":0.6491671204566956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5864959955215454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4885443150997162},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4745683968067169},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45307374000549316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4025813341140747},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.35853883624076843}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6491671204566956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5864959955215454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4885443150997162},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4745683968067169},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45307374000549316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4025813341140747},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.35853883624076843}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s11222-024-10486-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-024-10486-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-024-10486-6.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmh:oai:research-information.bris.ac.uk:publications/32209ca1-4f5d-46cc-8c53-5035b3e0fbe4","is_oa":true,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/32209ca1-4f5d-46cc-8c53-5035b3e0fbe4","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Stockman, S, Lawson, D J & Werner, M 2024, 'SB-ETAS : using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences', Statistics and Computing, vol. 34, no. 5, 174. https://doi.org/10.1007/s11222-024-10486-6","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire/32209ca1-4f5d-46cc-8c53-5035b3e0fbe4","is_oa":true,"landing_page_url":"https://hdl.handle.net/1983/32209ca1-4f5d-46cc-8c53-5035b3e0fbe4","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"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":"Stockman, S, Lawson, D J & Werner, M 2024, 'SB-ETAS : using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences', Statistics and Computing, vol. 34, no. 5, 174. https://doi.org/10.1007/s11222-024-10486-6","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s11222-024-10486-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-024-10486-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-024-10486-6.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2439283868","display_name":null,"funder_award_id":"G24AP00059","funder_id":"https://openalex.org/F4320332183","funder_display_name":"U.S. Geological Survey"},{"id":"https://openalex.org/G4263752315","display_name":null,"funder_award_id":"Ref EP/S023569/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4300216332","display_name":null,"funder_award_id":"821115","funder_id":"https://openalex.org/F4320335254","funder_display_name":"Horizon 2020"}],"funders":[{"id":"https://openalex.org/F4320332183","display_name":"U.S. Geological Survey","ror":"https://ror.org/035a68863"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320335254","display_name":"Horizon 2020","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402010817.pdf","grobid_xml":"https://content.openalex.org/works/W4402010817.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W124974610","https://openalex.org/W1580131890","https://openalex.org/W1591315510","https://openalex.org/W1964710995","https://openalex.org/W1968540183","https://openalex.org/W1972754097","https://openalex.org/W1995834672","https://openalex.org/W1999287311","https://openalex.org/W2026701305","https://openalex.org/W2028944227","https://openalex.org/W2045878033","https://openalex.org/W2045973738","https://openalex.org/W2064758233","https://openalex.org/W2065518921","https://openalex.org/W2069849731","https://openalex.org/W2078711966","https://openalex.org/W2085512286","https://openalex.org/W2085860135","https://openalex.org/W2091473165","https://openalex.org/W2098240499","https://openalex.org/W2109638305","https://openalex.org/W2116416291","https://openalex.org/W2117004425","https://openalex.org/W2118686689","https://openalex.org/W2130232835","https://openalex.org/W2135359991","https://openalex.org/W2142524879","https://openalex.org/W2147769040","https://openalex.org/W2148407447","https://openalex.org/W2291000087","https://openalex.org/W2340515955","https://openalex.org/W2508884334","https://openalex.org/W2560409346","https://openalex.org/W2592775008","https://openalex.org/W2594309842","https://openalex.org/W2594420594","https://openalex.org/W2729994464","https://openalex.org/W2747173499","https://openalex.org/W2791205985","https://openalex.org/W2807852313","https://openalex.org/W2808419019","https://openalex.org/W2808476530","https://openalex.org/W2898778909","https://openalex.org/W2903919837","https://openalex.org/W2907292342","https://openalex.org/W2935862809","https://openalex.org/W2952596119","https://openalex.org/W2955272954","https://openalex.org/W2965546532","https://openalex.org/W2972019283","https://openalex.org/W2973152437","https://openalex.org/W2990175406","https://openalex.org/W3031514878","https://openalex.org/W3032356321","https://openalex.org/W3037150409","https://openalex.org/W3106682895","https://openalex.org/W3140227887","https://openalex.org/W3162220961","https://openalex.org/W3201546928","https://openalex.org/W4292236074","https://openalex.org/W4324130795","https://openalex.org/W4386596682","https://openalex.org/W4394751847","https://openalex.org/W6639204077","https://openalex.org/W6776804597"],"related_works":["https://openalex.org/W2372267530","https://openalex.org/W2969189870","https://openalex.org/W2965643117","https://openalex.org/W4303857162","https://openalex.org/W2407375987","https://openalex.org/W3049691116","https://openalex.org/W2505726097","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W3081214562"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"rapid":[2],"growth":[3,39],"of":[4,21,25,135,213],"earthquake":[5,34,129,196,249],"catalogs,":[6,130,197],"driven":[7],"by":[8,261],"machine":[9],"learning-based":[10],"phase":[11],"picking":[12],"and":[13,72,253],"denser":[14],"seismic":[15],"networks,":[16],"calls":[17],"for":[18,96,151,201,216,256],"the":[19,30,49,63,73,97,125,154,240,263],"application":[20],"a":[22,91,147,225,228,267],"broader":[23],"range":[24],"models":[26,44,82,260],"to":[27,47,75,84,113,171,191,193,206,251,265],"determine":[28],"whether":[29],"new":[31],"data":[32,51],"enhances":[33],"forecasting":[35,43],"capabilities.":[36],"Additionally,":[37],"this":[38,217,244],"demands":[40],"that":[41,145,230],"existing":[42],"efficiently":[45],"scale":[46],"handle":[48],"increased":[50],"volume.":[52],"Approximate":[53],"inference":[54,77,94,152],"methods":[55],"such":[56,198],"as":[57,199],",":[58],"which":[59],"is":[60],"based":[61,93,149,246],"on":[62,78,224],"Integrated":[64],"nested":[65],"Laplace":[66],"approximation,":[67],"offer":[68],"improved":[69],"computational":[70],"efficiencies":[71],"ability":[74],"perform":[76],"more":[79,258],"complex":[80,259],"point-process":[81],"compared":[83,139],"traditional":[85],"MCMC":[86,122],"approaches.":[87],"We":[88],"present":[89],"SB-ETAS:":[90],"simulation":[92,148,245],"procedure":[95,150],"epidemic-type":[98],"aftershock":[99],"sequence":[100],"(ETAS)":[101],"model.":[102],"This":[103,187],"approximate":[104],"Bayesian":[105,211],"method":[106],"uses":[107],"sequential":[108],"neural":[109],"posterior":[110,115,137],"estimation":[111],"(SNPE)":[112],"learn":[114],"distributions":[116,138],"from":[117,156],"simulations,":[118],"rather":[119],"than":[120,221],"typical":[121],"sampling":[123],"using":[124,146,237],"likelihood.":[126],"On":[127],"synthetic":[128],"SB-ETAS":[131,208],"provides":[132],"better":[133],"coverage":[134],"ETAS":[136,214,242],"with":[140],".":[141,186],"Furthermore,":[142],"we":[143],"demonstrate":[144],"improves":[153],"scalability":[155],"$$\\mathcal":[157,172],"{O}(n^2)$$":[158],"<mml:math":[159,175],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[160,176],"<mml:mrow>":[161,177],"<mml:mi>O</mml:mi>":[162,178],"<mml:mo>(</mml:mo>":[163,179],"<mml:msup>":[164],"<mml:mi>n</mml:mi>":[165,180,182],"<mml:mn>2</mml:mn>":[166],"</mml:msup>":[167],"<mml:mo>)</mml:mo>":[168,183],"</mml:mrow>":[169,184],"</mml:math>":[170,185],"{O}(n\\log":[173],"n)$$":[174],"<mml:mo>log</mml:mo>":[181],"makes":[188],"it":[189],"feasible":[190],"fit":[192],"very":[194],"large":[195],"one":[200],"Southern":[202],"California":[203],"dating":[204],"back":[205],"1981.":[207],"can":[209],"find":[210],"estimates":[212],"parameters":[215,255],"catalog":[218],"in":[219],"less":[220],"10":[222],"h":[223],"standard":[226,241],"laptop,":[227],"task":[229],"would":[231],"have":[232],"taken":[233],"over":[234],"2":[235],"weeks":[236],"MCMC.":[238],"Beyond":[239],"model,":[243],"framework":[247],"allows":[248],"modellers":[250],"define":[252,266],"infer":[254],"much":[257],"removing":[262],"need":[264],"likelihood":[268],"function.":[269]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}
