{"id":"https://openalex.org/W4390574417","doi":"https://doi.org/10.1088/2632-2153/ad1af2","title":"Discovering interpretable physical models using symbolic regression and discrete exterior calculus","display_name":"Discovering interpretable physical models using symbolic regression and discrete exterior calculus","publication_year":2024,"publication_date":"2024-01-04","ids":{"openalex":"https://openalex.org/W4390574417","doi":"https://doi.org/10.1088/2632-2153/ad1af2"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/ad1af2","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad1af2","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad1af2/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad1af2/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060131413","display_name":"Simone Manti","orcid":"https://orcid.org/0000-0002-4060-0620"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Simone Manti","raw_affiliation_strings":["Mechanical and Production Engineering, Aarhus University, Inge Lehmanns Gade 10, Aarhus, 8000, DENMARK"],"raw_orcid":"https://orcid.org/0000-0002-4060-0620","affiliations":[{"raw_affiliation_string":"Mechanical and Production Engineering, Aarhus University, Inge Lehmanns Gade 10, Aarhus, 8000, DENMARK","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030428670","display_name":"Alessandro Lucantonio","orcid":"https://orcid.org/0000-0002-9807-5451"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Alessandro Lucantonio","raw_affiliation_strings":["Mechanical and Production Engineering, Aarhus University, Inge Lehmanns Gade 10, Aarhus, 8000, DENMARK"],"raw_orcid":"https://orcid.org/0000-0002-9807-5451","affiliations":[{"raw_affiliation_string":"Mechanical and Production Engineering, Aarhus University, Inge Lehmanns Gade 10, Aarhus, 8000, DENMARK","institution_ids":["https://openalex.org/I204337017"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030428670"],"corresponding_institution_ids":["https://openalex.org/I204337017"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":0.7946,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66637962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"5","issue":"1","first_page":"015005","last_page":"015005"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9864000082015991,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9550999999046326,"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/calculus","display_name":"Calculus (dental)","score":0.54557204246521},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5346433520317078},{"id":"https://openalex.org/keywords/symbolic-regression","display_name":"Symbolic regression","score":0.4775589108467102},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4621011018753052},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4479401707649231},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42425522208213806},{"id":"https://openalex.org/keywords/algebra-over-a-field","display_name":"Algebra over a field","score":0.3464605212211609},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28210869431495667},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2632228434085846},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.14273375272750854},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06543651223182678}],"concepts":[{"id":"https://openalex.org/C2777686260","wikidata":"https://www.wikidata.org/wiki/Q144037","display_name":"Calculus (dental)","level":2,"score":0.54557204246521},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5346433520317078},{"id":"https://openalex.org/C2776400721","wikidata":"https://www.wikidata.org/wiki/Q18171762","display_name":"Symbolic regression","level":3,"score":0.4775589108467102},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4621011018753052},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4479401707649231},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42425522208213806},{"id":"https://openalex.org/C136119220","wikidata":"https://www.wikidata.org/wiki/Q1000660","display_name":"Algebra over a field","level":2,"score":0.3464605212211609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28210869431495667},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2632228434085846},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.14273375272750854},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06543651223182678},{"id":"https://openalex.org/C199343813","wikidata":"https://www.wikidata.org/wiki/Q12128","display_name":"Dentistry","level":1,"score":0.0},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2632-2153/ad1af2","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad1af2","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad1af2/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/1a8f03cb-1a2c-4a80-9237-9c69f0e12d62","is_oa":true,"landing_page_url":"https://pure.au.dk/portal/en/publications/1a8f03cb-1a2c-4a80-9237-9c69f0e12d62","pdf_url":"https://pure.au.dk/ws/files/421787635/Manti_2024_Mach._Learn._Sci._Technol._5_015005.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Manti, S & Lucantonio, A 2024, 'Discovering interpretable physical models using symbolic regression and discrete exterior calculus', Machine Learning: Science and Technology, vol. 5, no. 1, 015005. https://doi.org/10.1088/2632-2153/ad1af2","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:88976e14543f49868169dde366e2e9cc","is_oa":true,"landing_page_url":"https://doaj.org/article/88976e14543f49868169dde366e2e9cc","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 5, Iss 1, p 015005 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/ad1af2","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/ad1af2","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/ad1af2/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2039602909","display_name":"AI-based Learning for Physical Simulation","funder_award_id":"101039481","funder_id":"https://openalex.org/F4320338453","funder_display_name":"HORIZON EUROPE European Research Council"},{"id":"https://openalex.org/G753438505","display_name":null,"funder_award_id":"101039481","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320322975","display_name":"Danish e-Infrastructure Cooperation","ror":"https://ror.org/03ge1nb22"},{"id":"https://openalex.org/F4320338453","display_name":"HORIZON EUROPE European Research Council","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4390574417.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1979769287","https://openalex.org/W2057734900","https://openalex.org/W2086776761","https://openalex.org/W2093828424","https://openalex.org/W2109042184","https://openalex.org/W2111819097","https://openalex.org/W2112311198","https://openalex.org/W2159314042","https://openalex.org/W2229156033","https://openalex.org/W2239232218","https://openalex.org/W2525748878","https://openalex.org/W2996020450","https://openalex.org/W3016401366","https://openalex.org/W3036548566","https://openalex.org/W3086784814","https://openalex.org/W3166835815","https://openalex.org/W3211856448","https://openalex.org/W4226320422","https://openalex.org/W4287996090","https://openalex.org/W4293842096","https://openalex.org/W4368303491","https://openalex.org/W4394666970","https://openalex.org/W6665241362","https://openalex.org/W6676279030","https://openalex.org/W6689579702","https://openalex.org/W6752296227","https://openalex.org/W6773942789","https://openalex.org/W6780561946","https://openalex.org/W6796097400","https://openalex.org/W6802929019","https://openalex.org/W6852384925","https://openalex.org/W6864522516"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"Abstract":[0],"Computational":[1],"modeling":[2],"is":[3],"a":[4,60,101,146],"key":[5],"resource":[6],"to":[7,21,33,95,135,144,198,211],"gather":[8],"insight":[9],"into":[10],"physical":[11,35,44,77,136,215],"systems":[12],"in":[13,205],"modern":[14],"scientific":[15],"research":[16],"and":[17,39,52,67,93,97,159,191],"engineering.":[18],"While":[19],"access":[20],"large":[22],"amount":[23],"of":[24,30,43,76,87,100,124,133,155,164,172,179,194,214],"data":[25],"has":[26],"fueled":[27],"the":[28,41,73,98,121,130,152,156,161,170,188,192,202],"use":[29,99],"machine":[31],"learning":[32],"recover":[34],"models":[36,48,78,85,158,178],"from":[37,80,182],"experiments":[38],"increase":[40],"accuracy":[42],"simulations,":[45],"purely":[46],"data-driven":[47],"have":[49],"limited":[50,112],"generalization":[51,110],"interpretability.":[53],"To":[54],"overcome":[55],"these":[56,84],"limitations,":[57],"we":[58,139,168],"propose":[59],"framework":[61],"that":[62,141,150],"combines":[63],"symbolic":[64,165],"regression":[65],"(SR)":[66],"discrete":[68,104,122],"exterior":[69],"calculus":[70],"(DEC)":[71],"for":[72,107,120],"automated":[74],"discovery":[75],"starting":[79],"experimental":[81,184],"data.":[82,114],"Since":[83],"consist":[86],"mathematical":[88,105,153],"expressions,":[89],"they":[90],"are":[91,128],"interpretable":[92],"amenable":[94],"analysis,":[96],"natural,":[102],"general-purpose":[103,200],"language":[106],"physics":[108,181],"favors":[109],"with":[111],"input":[113],"Importantly,":[115],"DEC":[116,142],"provides":[117],"building":[118],"blocks":[119],"analog":[123],"field":[125],"theories,":[126],"which":[127],"beyond":[129],"state-of-the-art":[131],"applications":[132],"SR":[134,148],"problems.":[137],"Further,":[138],"show":[140],"allows":[143],"implement":[145],"strongly-typed":[147],"procedure":[149],"guarantees":[151],"consistency":[154],"recovered":[157],"reduces":[160],"search":[162],"space":[163],"expressions.":[166],"Finally,":[167],"prove":[169],"effectiveness":[171],"our":[173],"methodology":[174],"by":[175],"re-discovering":[176],"three":[177],"continuum":[180],"synthetic":[183],"data:":[185],"Poisson":[186],"equation,":[187],"Euler\u2019s":[189],"elastica":[190],"equations":[193],"linear":[195],"elasticity.":[196],"Thanks":[197],"their":[199],"nature,":[201],"methods":[203],"developed":[204],"this":[206],"paper":[207],"may":[208],"be":[209],"applied":[210],"diverse":[212],"contexts":[213],"modeling.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
