{"id":"https://openalex.org/W3199355384","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534012","title":"Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems","display_name":"Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199355384","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534012","mag":"3199355384"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5087987814","display_name":"Manal Almaeen","orcid":"https://orcid.org/0009-0007-9645-331X"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Manal Almaeen","raw_affiliation_strings":["Old Dominion University, Norfolk, VA, USA"],"affiliations":[{"raw_affiliation_string":"Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020523339","display_name":"Yasir Alanazi","orcid":"https://orcid.org/0000-0002-4677-5018"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yasir Alanazi","raw_affiliation_strings":["Old Dominion University, Norfolk, VA, USA"],"affiliations":[{"raw_affiliation_string":"Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017193245","display_name":"N. Sato","orcid":"https://orcid.org/0000-0002-1535-6208"},"institutions":[{"id":"https://openalex.org/I29801172","display_name":"Thomas Jefferson National Accelerator Facility","ror":"https://ror.org/02vwzrd76","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I29801172","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nobuo Sato","raw_affiliation_strings":["Jefferson Lab, Theory Center, Newport News, VA, USA"],"affiliations":[{"raw_affiliation_string":"Jefferson Lab, Theory Center, Newport News, VA, USA","institution_ids":["https://openalex.org/I29801172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084803146","display_name":"Wally Melnitchouk","orcid":"https://orcid.org/0000-0002-9521-5973"},"institutions":[{"id":"https://openalex.org/I29801172","display_name":"Thomas Jefferson National Accelerator Facility","ror":"https://ror.org/02vwzrd76","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I29801172","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. Melnitchouk","raw_affiliation_strings":["Jefferson Lab, Theory Center, Newport News, VA, USA"],"affiliations":[{"raw_affiliation_string":"Jefferson Lab, Theory Center, Newport News, VA, USA","institution_ids":["https://openalex.org/I29801172"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058694585","display_name":"Michelle Kuchera","orcid":"https://orcid.org/0000-0002-9735-6147"},"institutions":[{"id":"https://openalex.org/I141720752","display_name":"Davidson College","ror":"https://ror.org/02f7k4z58","country_code":"US","type":"education","lineage":["https://openalex.org/I141720752"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michelle P. Kuchera","raw_affiliation_strings":["Davidson College, Davidson, NC, USA"],"affiliations":[{"raw_affiliation_string":"Davidson College, Davidson, NC, USA","institution_ids":["https://openalex.org/I141720752"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079316675","display_name":"Yaohang Li","orcid":"https://orcid.org/0000-0003-0178-1876"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaohang Li","raw_affiliation_strings":["Old Dominion University, Norfolk, VA, USA"],"affiliations":[{"raw_affiliation_string":"Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5087987814"],"corresponding_institution_ids":["https://openalex.org/I81365321"],"apc_list":null,"apc_paid":null,"fwci":0.9518,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8029715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9951000213623047,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9951000213623047,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9868000149726868,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.982200026512146,"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/autoencoder","display_name":"Autoencoder","score":0.9165195226669312},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.6982245445251465},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.6514752507209778},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5384893417358398},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5057733058929443},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48963600397109985},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.48722735047340393},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4185170531272888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38021382689476013},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3747583031654358},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3488907814025879},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.33675462007522583},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1890372633934021},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.16125419735908508},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.13692769408226013},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09981215000152588}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9165195226669312},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.6982245445251465},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.6514752507209778},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5384893417358398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5057733058929443},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48963600397109985},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.48722735047340393},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4185170531272888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38021382689476013},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3747583031654358},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3488907814025879},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33675462007522583},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1890372633934021},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.16125419735908508},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.13692769408226013},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09981215000152588},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7924744827","display_name":null,"funder_award_id":"DE-AC05-060R23177","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320309355","display_name":"Commonwealth of Virginia","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W624055699","https://openalex.org/W1574224119","https://openalex.org/W1579853615","https://openalex.org/W1959608418","https://openalex.org/W2029816571","https://openalex.org/W2102409316","https://openalex.org/W2114424556","https://openalex.org/W2127278384","https://openalex.org/W2166312616","https://openalex.org/W2225156818","https://openalex.org/W2574952845","https://openalex.org/W2607406448","https://openalex.org/W2896222781","https://openalex.org/W2952020389","https://openalex.org/W2962717353","https://openalex.org/W2964340499","https://openalex.org/W2992005611","https://openalex.org/W3002289736","https://openalex.org/W3016308847","https://openalex.org/W3091395212","https://openalex.org/W3096831136","https://openalex.org/W3101765447","https://openalex.org/W4287601418","https://openalex.org/W4289694518","https://openalex.org/W6634249487","https://openalex.org/W6640963894","https://openalex.org/W6675401909","https://openalex.org/W6688325169","https://openalex.org/W6753758835"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2331917905","https://openalex.org/W3155039083","https://openalex.org/W1970914699"],"abstract_inverted_index":{"Inverse":[0,35],"problems":[1],"-":[2,10],"using":[3],"measured":[4],"observations":[5],"to":[6,69,77,107],"determine":[7],"unknown":[8],"parameters":[9],"are":[11],"well":[12],"motivated":[13],"but":[14],"challenging":[15],"in":[16,109],"many":[17],"science":[18],"and":[19,49,56,60,94,97],"engineering":[20],"problems.":[21,46],"In":[22],"this":[23],"paper,":[24],"we":[25],"propose":[26],"an":[27,39],"end-to-end":[28],"deep":[29],"learning":[30],"framework,":[31],"the":[32,54,71,82,100],"Variational":[33],"Autoencoder":[34],"Mapper":[36],"(VAIM),":[37],"as":[38],"autoencoder-based":[40],"neural":[41,51],"network":[42],"architecture":[43],"for":[44,86,98],"inverse":[45,89,101],"The":[47],"encoder":[48],"decoder":[50],"networks":[52],"approximate":[53],"forward":[55],"backward":[57],"mapping,":[58],"respectively,":[59],"a":[61,110],"variational":[62],"latent":[63],"layer":[64],"is":[65],"incorporated":[66],"into":[67],"VAIM":[68,85],"learn":[70],"posterior":[72],"parameter":[73],"distributions":[74],"with":[75,91],"respect":[76],"given":[78],"observables.":[79],"We":[80],"demonstrate":[81],"effectiveness":[83],"of":[84,114],"several":[87],"toy":[88],"problems,":[90],"both":[92],"finite":[93],"infinite":[95],"solutions,":[96],"constructing":[99],"function":[102],"mapping":[103],"quantum":[104],"correlation":[105],"functions":[106],"observables":[108],"Quantum":[111],"Chromodynamics":[112],"analysis":[113],"nucleon":[115],"structure.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}