{"id":"https://openalex.org/W3194577116","doi":"https://doi.org/10.1109/ssp49050.2021.9513766","title":"Fast Bayesian Model Selection in Imaging Inverse Problems Using Residuals","display_name":"Fast Bayesian Model Selection in Imaging Inverse Problems Using Residuals","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3194577116","doi":"https://doi.org/10.1109/ssp49050.2021.9513766","mag":"3194577116"},"language":"en","primary_location":{"id":"doi:10.1109/ssp49050.2021.9513766","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513766","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050957190","display_name":"Ana F. Vidal","orcid":"https://orcid.org/0000-0002-1121-6195"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]},{"id":"https://openalex.org/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]}],"countries":["GB","MY"],"is_corresponding":true,"raw_author_name":"Ana Fernandez Vidal","raw_affiliation_strings":["Heriot-Watt University,School of Mathematical and Computer Sciences,Edinburgh,United Kingdom","School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Mathematical and Computer Sciences,Edinburgh,United Kingdom","institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210085930"]},{"raw_affiliation_string":"School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082169271","display_name":"Marcelo Pereyra","orcid":"https://orcid.org/0000-0001-6438-6772"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]},{"id":"https://openalex.org/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]},{"id":"https://openalex.org/I4210117017","display_name":"Maxwell Institute for Mathematical Sciences","ror":"https://ror.org/02tsqtg57","country_code":"GB","type":"facility","lineage":["https://openalex.org/I32062511","https://openalex.org/I4210117017","https://openalex.org/I98677209"]}],"countries":["GB","MY"],"is_corresponding":false,"raw_author_name":"Marcelo Pereyra","raw_affiliation_strings":["Heriot-Watt University,School of Mathematical and Computer Sciences,Edinburgh,United Kingdom","Maxwell Institute for Mathematical Sciences, Edinburgh, United Kingdom","School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Mathematical and Computer Sciences,Edinburgh,United Kingdom","institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210085930"]},{"raw_affiliation_string":"Maxwell Institute for Mathematical Sciences, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I4210117017"]},{"raw_affiliation_string":"School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036096413","display_name":"Alain Durmus","orcid":"https://orcid.org/0000-0002-2086-8611"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Alain Durmus","raw_affiliation_strings":["Université Paris-Saclay,CMLA - École Normale Supérieure Paris-Saclay, CNRS,Cachan,France,94235"],"affiliations":[{"raw_affiliation_string":"Université Paris-Saclay,CMLA - École Normale Supérieure Paris-Saclay, CNRS,Cachan,France,94235","institution_ids":["https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091811958","display_name":"Jean\u2010Fran\u00e7ois Giovannelli","orcid":"https://orcid.org/0000-0002-0372-9329"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I15057530","display_name":"Universit\u00e9 de Bordeaux","ror":"https://ror.org/057qpr032","country_code":"FR","type":"education","lineage":["https://openalex.org/I15057530"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Francois Giovannelli","raw_affiliation_strings":["IMS (Université de Bordeaux - CNRS - BINP),Talence,France"],"affiliations":[{"raw_affiliation_string":"IMS (Université de Bordeaux - CNRS - BINP),Talence,France","institution_ids":["https://openalex.org/I4210157089","https://openalex.org/I4210160189","https://openalex.org/I1294671590","https://openalex.org/I15057530"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050957190"],"corresponding_institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210085930"],"apc_list":null,"apc_paid":null,"fwci":0.1751,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45830505,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"18","issue":null,"first_page":"91","last_page":"95"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9955000281333923,"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/deblurring","display_name":"Deblurring","score":0.8375897407531738},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6259701251983643},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.6190699338912964},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6011063456535339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.564436137676239},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5542435646057129},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5138952732086182},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5073296427726746},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4897210896015167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45555007457733154},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42958033084869385},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4121590256690979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38633784651756287},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3610038757324219},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.3082095682621002},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.286399781703949},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2787485122680664},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27422910928726196},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.24575188755989075}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8375897407531738},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6259701251983643},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.6190699338912964},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6011063456535339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.564436137676239},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5542435646057129},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5138952732086182},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5073296427726746},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4897210896015167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45555007457733154},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42958033084869385},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4121590256690979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38633784651756287},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3610038757324219},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.3082095682621002},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.286399781703949},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2787485122680664},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27422910928726196},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.24575188755989075},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ssp49050.2021.9513766","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513766","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04551521v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04551521","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP), Jul 2021, Rio de Janeiro, Brazil. pp.91-95, ⟨10.1109/SSP49050.2021.9513766⟩","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8302899414","display_name":null,"funder_award_id":"EP/T007346/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1488903245","https://openalex.org/W1941028167","https://openalex.org/W1946620893","https://openalex.org/W2030524152","https://openalex.org/W2040609377","https://openalex.org/W2087416986","https://openalex.org/W2100705753","https://openalex.org/W2117076645","https://openalex.org/W2158128575","https://openalex.org/W2200649065","https://openalex.org/W2464084515","https://openalex.org/W2566924527","https://openalex.org/W2963490248","https://openalex.org/W2989866504","https://openalex.org/W3010196270","https://openalex.org/W3026009652","https://openalex.org/W3123857276","https://openalex.org/W6629358039","https://openalex.org/W6677459581","https://openalex.org/W6737101116","https://openalex.org/W6770414171","https://openalex.org/W6777320043"],"related_works":["https://openalex.org/W4205848364","https://openalex.org/W2134276905","https://openalex.org/W1503532423","https://openalex.org/W1967494390","https://openalex.org/W245717845","https://openalex.org/W3013496002","https://openalex.org/W2465363361","https://openalex.org/W2896820906","https://openalex.org/W2101542441","https://openalex.org/W1763060499"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,77,99],"fast":[4],"heuristic":[5,38],"for":[6],"comparing":[7],"Bayesian":[8,90],"models":[9,85],"to":[10,15,60],"solve":[11],"inverse":[12],"problems":[13,21],"related":[14],"signal":[16,28],"processing.":[17],"We":[18],"focus":[19],"on":[20,87],"that":[22,65],"are":[23],"convex":[24],"w.r.t.":[25],"the":[26,47,50,54,62,84],"unknown":[27],"and":[29,43],"where":[30,104],"no":[31],"ground":[32],"truth":[33],"is":[34,39,57,96],"available.":[35],"The":[36,93],"proposed":[37,94],"very":[40],"computationally":[41],"efficient":[42],"does":[44],"not":[45],"require":[46],"estimation":[48],"of":[49,83],"model":[51,55,69],"evidence.":[52],"Instead,":[53],"evidence":[56],"used":[58],"indirectly":[59],"set":[61],"regularisation":[63],"parameters":[64],"define":[66],"each":[67],"competing":[68],"by":[70,76],"maximum":[71],"marginal":[72],"likelihood":[73],"estimation,":[74],"followed":[75],"simple":[78],"likelihood-based":[79],"or":[80],"residual-based":[81],"comparison":[82],"based":[86],"their":[88],"empirical":[89],"maximum-a-posteriori":[91],"solutions.":[92],"methodology":[95],"illustrated":[97],"with":[98],"total-variation":[100],"image":[101],"deblurring":[102],"experiment,":[103],"it":[105],"performs":[106],"remarkably":[107],"well.":[108]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}