{"id":"https://openalex.org/W7131639936","doi":"https://doi.org/10.48550/arxiv.2602.21707","title":"Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries","display_name":"Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries","publication_year":2026,"publication_date":"2026-02-25","ids":{"openalex":"https://openalex.org/W7131639936","doi":"https://doi.org/10.48550/arxiv.2602.21707"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.21707","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126858952","display_name":"Joshua Schulz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schulz, Joshua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126946129","display_name":"David Schote","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schote, David","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126891364","display_name":"Christoph Kolbitsch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kolbitsch, Christoph","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033749693","display_name":"Kostas Papafitsoros","orcid":"https://orcid.org/0000-0001-9691-4576"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Papafitsoros, Kostas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126884509","display_name":"Andreas Kofler","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kofler, Andreas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.5249000191688538,"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"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.5249000191688538,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.20419999957084656,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.04699999839067459,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/interpretability","display_name":"Interpretability","score":0.8245000243186951},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6876000165939331},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6223999857902527},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5519000291824341},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5467000007629395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5199000239372253},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.49480000138282776},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4099999964237213}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8245000243186951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6884999871253967},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6876000165939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6689000129699707},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6223999857902527},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5519000291824341},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5467000007629395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5199000239372253},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.49480000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.40130001306533813},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.38749998807907104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3720000088214874},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.262800008058548},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25220000743865967},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.21707","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.21707","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.21707","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.21707","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7526288628578186}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"State-of-the-art":[0],"learned":[1,147],"reconstruction":[2,29,164],"methods":[3],"often":[4],"rely":[5],"on":[6,24,34,101,123,130,156],"black-box":[7],"modules":[8],"that,":[9],"despite":[10],"their":[11,17],"strong":[12],"performance,":[13],"raise":[14],"questions":[15],"about":[16],"interpretability":[18],"and":[19,58,90,125],"robustness.":[20],"Here,":[21],"we":[22,62,150],"build":[23],"a":[25,39,110],"recently":[26],"proposed":[27,134],"image":[28],"method,":[30],"which":[31,149],"is":[32,113],"based":[33],"embedding":[35],"data-driven":[36],"information":[37],"into":[38],"model-based":[40,163],"convolutional":[41,78],"dictionary":[42,79,112],"regularization":[43],"via":[44],"neural":[45],"network-inferred":[46],"spatially":[47],"adaptive":[48],"sparsity":[49],"level":[50],"maps.":[51],"By":[52],"means":[53],"of":[54,108],"improved":[55],"network":[56],"design":[57],"dedicated":[59],"training":[60,157],"strategies,":[61],"extend":[63],"the":[64,73,77,106,118,131,133,139,145],"method":[65,86,135],"to":[66,75,87,93,144,152,160],"achieve":[67],"filter-permutation":[68],"invariance":[69],"as":[70,72],"well":[71],"possibility":[74],"change":[76],"at":[80],"inference":[81],"time.":[82],"We":[83,115],"apply":[84],"our":[85],"low-field":[88],"MRI":[89],"compare":[91],"it":[92],"several":[94],"other":[95,146],"recent":[96],"deep":[97],"learning-based":[98],"methods,":[99,148],"also":[100],"in":[102],"vivo":[103],"data,":[104],"where":[105],"benefit":[107],"using":[109],"different":[111],"demonstrated.":[114],"further":[116],"assess":[117],"method's":[119],"robustness":[120],"when":[121],"tested":[122,129],"in-":[124],"out-of-distribution":[126],"data.":[127],"When":[128],"latter,":[132],"suffers":[136],"less":[137],"from":[138],"data":[140,158],"distribution":[141],"shift":[142],"compared":[143],"attribute":[151],"its":[153,161],"reduced":[154],"reliance":[155],"due":[159],"underlying":[162],"component.":[165]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-27T00:00:00"}
