{"id":"https://openalex.org/W4392271507","doi":"https://doi.org/10.48550/arxiv.2402.17603","title":"TRIPs-Py: Techniques for Regularization of Inverse Problems in Python","display_name":"TRIPs-Py: Techniques for Regularization of Inverse Problems in Python","publication_year":2024,"publication_date":"2024-02-27","ids":{"openalex":"https://openalex.org/W4392271507","doi":"https://doi.org/10.48550/arxiv.2402.17603"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2402.17603","pdf_url":"https://arxiv.org/pdf/2402.17603","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2402.17603","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065506133","display_name":"Mirjeta Pasha","orcid":"https://orcid.org/0000-0003-4249-2421"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pasha, Mirjeta","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004148217","display_name":"Silvia Gazzola","orcid":"https://orcid.org/0000-0001-9588-0896"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gazzola, Silvia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077507169","display_name":"Connor Sanderford","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanderford, Connor","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061890777","display_name":"Ugochukwu O. Ugwu","orcid":"https://orcid.org/0000-0002-7743-2544"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ugwu, Ugochukwu O.","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":84},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.8866,"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"}},"topics":[{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.8866,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.8188,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.7896,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python","score":0.78703415},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization","score":0.4699975}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.78703415},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.6003879},{"id":"https://openalex.org/C157085824","wikidata":"https://www.wikidata.org/wiki/Q2384809","display_name":"TRIPS architecture","level":2,"score":0.53367186},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4699975},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4035407},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3960458},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.23297516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20487532},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06775215},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.047785133}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2402.17603","pdf_url":"https://arxiv.org/pdf/2402.17603","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2402.17603","pdf_url":"https://arxiv.org/pdf/2402.17603","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4297799326","https://openalex.org/W4287027380","https://openalex.org/W4224254130","https://openalex.org/W3187193180","https://openalex.org/W3116064965","https://openalex.org/W2807758032","https://openalex.org/W2341492732","https://openalex.org/W2152103536","https://openalex.org/W1699080303","https://openalex.org/W106542691"],"abstract_inverted_index":{"In":[0],"this":[1,166],"paper,":[2],"we":[3],"describe":[4],"TRIPs-Py,":[5],"a":[6,45],"new":[7],"Python":[8,162],"package":[9,23,164],"of":[10,21,48,105,143,155,165],"linear":[11],"discrete":[12],"inverse":[13,35],"problems":[14,42,108,122,125],"solvers":[15,51,78,95],"and":[16,33,37,65,67,76,88,116,173],"test":[17,41,107,121,150],"problems.":[18,151],"The":[19,50],"goal":[20],"the":[22,101,106,136,141,144,148,153,160],"is":[24,159],"two-fold:":[25],"1)":[26],"to":[27,39,99,134],"provide":[28],"tools":[29],"for":[30,79],"solving":[31],"small":[32],"large-scale":[34],"problems,":[36],"2)":[38],"introduce":[40],"arising":[43],"from":[44,112],"wide":[46],"range":[47],"applications.":[49],"available":[52],"in":[53,109,126],"TRIPs-Py":[54,110,158],"include":[55],"direct":[56],"regularization":[57,69,102],"methods":[58,75,146],"(such":[59,71],"as":[60,72,138,140],"truncated":[61],"singular":[62],"value":[63],"decomposition":[64],"Tikhonov)":[66],"iterative":[68],"techniques":[70],"Krylov":[73],"subspace":[74],"recent":[77],"$\\ell_p$-$\\ell_q$":[80],"formulations,":[81],"which":[82,168],"enforce":[83],"sparse":[84],"or":[85],"edge-preserving":[86],"solutions":[87],"handle":[89],"different":[90],"noise":[91],"types).":[92],"All":[93],"our":[94,156],"have":[96],"built-in":[97],"strategies":[98],"define":[100],"parameter(s).":[103],"Some":[104],"arise":[111],"simulated":[113],"image":[114],"deblurring":[115],"computerized":[117,128],"tomography,":[118],"while":[119],"other":[120],"model":[123],"realistic":[124],"dynamic":[127],"tomography.":[129],"Numerical":[130],"examples":[131],"are":[132],"included":[133],"illustrate":[135],"usage":[137],"well":[139],"performance":[142],"described":[145],"on":[147],"provided":[149],"To":[152],"best":[154],"knowledge,":[157],"first":[161],"software":[163],"kind,":[167],"may":[169],"serve":[170],"both":[171],"research":[172],"didactical":[174],"purposes.":[175]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4392271507","counts_by_year":[],"updated_date":"2024-12-10T23:49:16.746523","created_date":"2024-03-05"}