{"id":"https://openalex.org/W4226061793","doi":"https://doi.org/10.1137/21m1442747","title":"Efficient Approximation of SDEs Driven by Countably Dimensional Wiener Process and Poisson Random Measure","display_name":"Efficient Approximation of SDEs Driven by Countably Dimensional Wiener Process and Poisson Random Measure","publication_year":2022,"publication_date":"2022-04-01","ids":{"openalex":"https://openalex.org/W4226061793","doi":"https://doi.org/10.1137/21m1442747","mag":"3191378762"},"language":"en","primary_location":{"id":"doi:10.1137/21m1442747","is_oa":false,"landing_page_url":"https://doi.org/10.1137/21m1442747","pdf_url":null,"source":{"id":"https://openalex.org/S203348814","display_name":"SIAM Journal on Numerical Analysis","issn_l":"0036-1429","issn":["0036-1429","1095-7170"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Numerical Analysis","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2108.02394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038984082","display_name":"Pawe\u0142 Przyby\u0142owicz","orcid":"https://orcid.org/0000-0001-7870-8605"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pawe\u0142 Przyby\u0142owicz","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7870-8605","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088506734","display_name":"Micha\u0142 Sobieraj","orcid":"https://orcid.org/0000-0002-3441-3378"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Micha\u0142 Sobieraj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101835602","display_name":"Lukasz T. Stepien","orcid":"https://orcid.org/0000-0002-8038-6091"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u0141ukasz St\u0229pie\u0144","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038984082"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6761,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84444107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"60","issue":"2","first_page":"824","last_page":"855"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10067","display_name":"Stochastic processes and financial applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10067","display_name":"Stochastic processes and financial applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9675999879837036,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.8322255611419678},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.8286747932434082},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6903308033943176},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5565911531448364},{"id":"https://openalex.org/keywords/wiener-process","display_name":"Wiener process","score":0.5288444757461548},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5145742297172546},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.4990043640136719},{"id":"https://openalex.org/keywords/stochastic-differential-equation","display_name":"Stochastic differential equation","score":0.4704928398132324},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4489428997039795},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4269120395183563},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.346950888633728},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.19977611303329468},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.08711513876914978}],"concepts":[{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.8322255611419678},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.8286747932434082},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6903308033943176},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5565911531448364},{"id":"https://openalex.org/C60391097","wikidata":"https://www.wikidata.org/wiki/Q1056809","display_name":"Wiener process","level":2,"score":0.5288444757461548},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5145742297172546},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.4990043640136719},{"id":"https://openalex.org/C51955184","wikidata":"https://www.wikidata.org/wiki/Q1545585","display_name":"Stochastic differential equation","level":2,"score":0.4704928398132324},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4489428997039795},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4269120395183563},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.346950888633728},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.19977611303329468},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.08711513876914978},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1137/21m1442747","is_oa":false,"landing_page_url":"https://doi.org/10.1137/21m1442747","pdf_url":null,"source":{"id":"https://openalex.org/S203348814","display_name":"SIAM Journal on Numerical Analysis","issn_l":"0036-1429","issn":["0036-1429","1095-7170"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Numerical Analysis","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2108.02394","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.02394","pdf_url":"https://arxiv.org/pdf/2108.02394","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"mag:3191378762","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2108.02394","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2108.02394","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.02394","pdf_url":"https://arxiv.org/pdf/2108.02394","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W204981070","https://openalex.org/W578766863","https://openalex.org/W1503185336","https://openalex.org/W1545518728","https://openalex.org/W1554388601","https://openalex.org/W1990460919","https://openalex.org/W1995522593","https://openalex.org/W2013538100","https://openalex.org/W2020481578","https://openalex.org/W2031383357","https://openalex.org/W2033608413","https://openalex.org/W2034692694","https://openalex.org/W2124633737","https://openalex.org/W2129849411","https://openalex.org/W2304605012","https://openalex.org/W2584500302","https://openalex.org/W2607218206","https://openalex.org/W2725768875","https://openalex.org/W2793754387","https://openalex.org/W2806513737","https://openalex.org/W2891854843","https://openalex.org/W2892350531","https://openalex.org/W2899612018","https://openalex.org/W2908495121","https://openalex.org/W2908847000","https://openalex.org/W3020533307","https://openalex.org/W3021898623","https://openalex.org/W3044441106","https://openalex.org/W3089503285","https://openalex.org/W3136686389","https://openalex.org/W4235679898","https://openalex.org/W4255534777"],"related_works":["https://openalex.org/W143502885","https://openalex.org/W42113618","https://openalex.org/W2781926166","https://openalex.org/W353781384","https://openalex.org/W90333354","https://openalex.org/W2965673486","https://openalex.org/W2527752610","https://openalex.org/W2035506987","https://openalex.org/W1529778964","https://openalex.org/W4294558488"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"deal":[4],"with":[5,22],"pointwise":[6],"approximation":[7],"of":[8,10,74],"solutions":[9],"stochastic":[11],"differential":[12],"equations":[13],"(SDEs)":[14],"driven":[15],"by":[16,26],"an":[17],"infinite":[18],"dimensional":[19],"Wiener":[20],"process,":[21],"additional":[23],"jumps":[24],"generated":[25],"a":[27],"Poisson":[28],"random":[29],"measure.":[30],"Further":[31],"investigations":[32],"contain":[33],"upper":[34,52],"error":[35],"bounds":[36,55],"for":[37,56],"the":[38,61,67],"proposed":[39],"truncated":[40],"dimension":[41],"randomized":[42],"Euler":[43],"scheme.":[44],"We":[45],"also":[46,82],"establish":[47],"matching":[48],"(up":[49],"to":[50],"constants)":[51],"and":[53,58],"lower":[54],"$\\varepsilon$-complexity":[57],"show":[59],"that":[60],"defined":[62],"algorithm":[63],"is":[64],"optimal":[65],"in":[66],"information-based":[68],"complexity":[69],"(IBC)":[70],"sense.":[71],"Finally,":[72],"results":[73],"numerical":[75],"experiments":[76],"performed":[77],"via":[78],"GPU":[79],"architecture":[80],"are":[81],"reported.":[83]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}