{"id":"https://openalex.org/W4313592055","doi":"https://doi.org/10.1088/2632-2153/acb03e","title":"Learning the dynamics of particle-based systems with Lagrangian graph neural networks","display_name":"Learning the dynamics of particle-based systems with Lagrangian graph neural networks","publication_year":2023,"publication_date":"2023-01-04","ids":{"openalex":"https://openalex.org/W4313592055","doi":"https://doi.org/10.1088/2632-2153/acb03e"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/acb03e","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acb03e","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acb03e/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/acb03e/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006461542","display_name":"Ravinder Bhattoo","orcid":null},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ravinder Bhattoo","raw_affiliation_strings":["Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054697900","display_name":"Sayan Ranu","orcid":"https://orcid.org/0000-0003-4147-9372"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sayan Ranu","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","institution_ids":["https://openalex.org/I68891433"]},{"raw_affiliation_string":"Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065129881","display_name":"N. M. Anoop Krishnan","orcid":"https://orcid.org/0000-0003-1500-4947"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"N M Anoop Krishnan","raw_affiliation_strings":["Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","institution_ids":["https://openalex.org/I68891433"]},{"raw_affiliation_string":"Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006461542","https://openalex.org/A5054697900","https://openalex.org/A5065129881"],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":1.2633,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.76207685,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"4","issue":"1","first_page":"015003","last_page":"015003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9695000052452087,"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/T10409","display_name":"Fuel Cells and Related Materials","score":0.9276999831199646,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.753054141998291},{"id":"https://openalex.org/keywords/lagrangian","display_name":"Lagrangian","score":0.6185761094093323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6062027215957642},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.5903424620628357},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5350068211555481},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5257944464683533},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5190309286117554},{"id":"https://openalex.org/keywords/inductive-bias","display_name":"Inductive bias","score":0.5159124135971069},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.47025027871131897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4666825234889984},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.44543930888175964},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.4440978467464447},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4270935654640198},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33598947525024414},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2339356243610382},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15030288696289062},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.1149352490901947}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.753054141998291},{"id":"https://openalex.org/C53469067","wikidata":"https://www.wikidata.org/wiki/Q505735","display_name":"Lagrangian","level":2,"score":0.6185761094093323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6062027215957642},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.5903424620628357},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5350068211555481},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5257944464683533},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5190309286117554},{"id":"https://openalex.org/C197352929","wikidata":"https://www.wikidata.org/wiki/Q1074074","display_name":"Inductive bias","level":4,"score":0.5159124135971069},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.47025027871131897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4666825234889984},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.44543930888175964},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.4440978467464447},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4270935654640198},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33598947525024414},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2339356243610382},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15030288696289062},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.1149352490901947},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1088/2632-2153/acb03e","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acb03e","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acb03e/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:doaj.org/article:6bbca1e256934faebdb91543242408fd","is_oa":true,"landing_page_url":"https://doaj.org/article/6bbca1e256934faebdb91543242408fd","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 4, Iss 1, p 015003 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/acb03e","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acb03e","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acb03e/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":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313592055.pdf","grobid_xml":"https://content.openalex.org/works/W4313592055.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2948680363","https://openalex.org/W2962730452","https://openalex.org/W3007175346","https://openalex.org/W3007913393","https://openalex.org/W3021457401","https://openalex.org/W3029817982","https://openalex.org/W3036548566","https://openalex.org/W3100611487","https://openalex.org/W3153522897","https://openalex.org/W3163857962","https://openalex.org/W3163993681","https://openalex.org/W4205254860","https://openalex.org/W4225983190","https://openalex.org/W4287328697","https://openalex.org/W4288102126","https://openalex.org/W4294508621","https://openalex.org/W4295371972","https://openalex.org/W4321361265","https://openalex.org/W6758539823","https://openalex.org/W6763340073","https://openalex.org/W6768331551","https://openalex.org/W6774033856","https://openalex.org/W6774655639","https://openalex.org/W6775127026","https://openalex.org/W6780256688","https://openalex.org/W6780561946","https://openalex.org/W6784408391","https://openalex.org/W6786413338","https://openalex.org/W6798099128","https://openalex.org/W6810393319"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4378220270","https://openalex.org/W4310745665","https://openalex.org/W2996487136","https://openalex.org/W4297631130","https://openalex.org/W4313592055"],"abstract_inverted_index":{"Abstract":[0],"Physical":[1],"systems":[2,80,111,124,193],"are":[3,126],"commonly":[4],"represented":[5],"as":[6,31,89],"a":[7,46,58,67,131,185],"combination":[8],"of":[9,14,26,40,66,106,114,137,157,164,191],"particles,":[10],"the":[11,17,24,32,38,64,72,103,107,118,129,141,162,179,189],"individual":[12],"dynamics":[13,39,190],"which":[15,167],"govern":[16],"system":[18,69,108],"dynamics.":[19],"However,":[20],"traditional":[21],"approaches":[22],"require":[23],"knowledge":[25],"several":[27],"abstract":[28],"quantities":[29],"such":[30,88],"energy":[33],"or":[34],"force":[35],"to":[36,62,145],"infer":[37],"these":[41],"particles.":[42],"Here,":[43],"we":[44,160],"present":[45],"framework,":[47],"namely,":[48],"Lagrangian":[49,65,91],"graph":[50,135],"neural":[51,92],"network":[52,93],"(":[53,94],"LGnn":[54,85,138,165,181],"),":[55],"that":[56,125],"provides":[57,169],"strong":[59],"inductive":[60],"bias":[61],"learn":[63],"particle-based":[68],"directly":[70,168],"from":[71,195],"trajectory.":[73],"We":[74,100],"test":[75],"our":[76],"approach":[77],"on":[78,152,172],"challenging":[79],"with":[81,97,147],"constraints":[82],"and":[83,121,174],"drag\u2014":[84],"outperforms":[86],"baselines":[87],"feed-forward":[90],"Lnn":[95,146],")":[96],"improved":[98],"performance.":[99],"also":[101,122],"show":[102,161],"zero-shot":[104],"generalizability":[105],"by":[109,128,178],"simulating":[110],"two":[112],"orders":[113],"magnitude":[115],"larger":[116],"than":[117],"trained":[119],"one":[120],"hybrid":[123],"unseen":[127],"model,":[130],"unique":[132],"feature.":[133],"The":[134],"architecture":[136],"significantly":[139],"simplifies":[140],"learning":[142],"in":[143],"comparison":[144],"\u223c25":[148],"times":[149,154],"better":[150],"performance":[151],"\u223c20":[153],"smaller":[155],"amounts":[156],"data.":[158],"Finally,":[159],"interpretability":[163],",":[166],"physical":[170,192],"insights":[171],"drag":[173],"constraint":[175],"forces":[176],"learned":[177],"model.":[180],"can":[182],"thus":[183],"provide":[184],"fillip":[186],"toward":[187],"understanding":[188],"purely":[194],"observable":[196],"quantities.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}