{"id":"https://openalex.org/W7160396429","doi":"https://doi.org/10.48550/arxiv.2605.03386","title":"Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting","display_name":"Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160396429","doi":"https://doi.org/10.48550/arxiv.2605.03386"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.03386","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03386","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.03386","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135514328","display_name":"Xiao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135530424","display_name":"Yafei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yafei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135454294","display_name":"Ruixiang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ruixiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135434417","display_name":"Wei Wei","orcid":"https://orcid.org/0000-0003-4777-7645"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121174957","display_name":"Shuo He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135455174","display_name":"Mingliang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Mingliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"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":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/T11206","display_name":"Model Reduction and Neural Networks","score":0.5644999742507935,"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":0.5644999742507935,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.10140000283718109,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.04039999842643738,"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/ode","display_name":"Ode","score":0.8144999742507935},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5598000288009644},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.5575000047683716},{"id":"https://openalex.org/keywords/ordinary-differential-equation","display_name":"Ordinary differential equation","score":0.5299999713897705},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49399998784065247},{"id":"https://openalex.org/keywords/truncation-error","display_name":"Truncation error","score":0.4668000042438507},{"id":"https://openalex.org/keywords/truncation","display_name":"Truncation (statistics)","score":0.4262999892234802},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.414900004863739}],"concepts":[{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.8144999742507935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5813000202178955},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5598000288009644},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.5575000047683716},{"id":"https://openalex.org/C51544822","wikidata":"https://www.wikidata.org/wiki/Q465274","display_name":"Ordinary differential equation","level":3,"score":0.5299999713897705},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C104942944","wikidata":"https://www.wikidata.org/wiki/Q3434686","display_name":"Truncation error","level":2,"score":0.4668000042438507},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.414900004863739},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3653999865055084},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33230000734329224},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.328000009059906},{"id":"https://openalex.org/C2778671503","wikidata":"https://www.wikidata.org/wiki/Q7542110","display_name":"Slow manifold","level":3,"score":0.32710000872612},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30559998750686646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.288100004196167},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C78045399","wikidata":"https://www.wikidata.org/wiki/Q11214","display_name":"Differential equation","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C93779851","wikidata":"https://www.wikidata.org/wiki/Q271977","display_name":"Partial differential equation","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.25440001487731934},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.03386","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03386","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.03386","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03386","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5606178641319275}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spatiotemporal":[0],"forecasting":[1],"in":[2,142,198],"physical":[3],"systems,":[4],"such":[5,68],"as":[6,104,118],"large-scale":[7,168],"traffic":[8],"networks,":[9],"requires":[10],"modeling":[11],"a":[12,105,129,148],"dual":[13],"dynamic:":[14],"continuous":[15,139],"macroscopic":[16],"rhythms":[17],"and":[18,75],"discrete,":[19],"unpredictable":[20],"microscopic":[21],"shocks.":[22],"While":[23],"Neural":[24,96],"Ordinary":[25],"Differential":[26],"Equations":[27],"(ODEs)":[28],"excel":[29],"at":[30,153],"capturing":[31],"smooth":[32],"evolution,":[33],"their":[34],"inherent":[35],"Lipschitz":[36],"continuity":[37],"constraints":[38,197],"inevitably":[39],"cause":[40],"severe":[41],"over-smoothing":[42],"when":[43],"confronting":[44],"abrupt":[45],"anomalies.":[46,85],"Recent":[47],"physics-informed":[48],"methods":[49],"attempt":[50],"to":[51,59,84,107,190,193],"bypass":[52],"this":[53,88],"by":[54],"penalizing":[55],"numerical":[56,102],"integration":[57,181],"errors":[58],"enforce":[60],"manifold":[61,160],"smoothness.":[62],"However,":[63],"we":[64,91,110],"mathematically":[65],"reveal":[66],"that":[67],"rigid":[69],"regularization":[70],"inherently":[71],"triggers":[72],"gradient":[73],"conflicts":[74],"``attention":[76],"collapse,''":[77],"stripping":[78],"the":[79,113,126,188],"model":[80,189],"of":[81],"its":[82],"sensitivity":[83],"To":[86],"resolve":[87],"continuity-shock":[89],"dilemma,":[90],"propose":[92],"Local":[93,114],"Truncation":[94,115],"Error-Guided":[95],"ODEs":[97],"(LTE-ODE).":[98],"Rather":[99],"than":[100],"treating":[101],"error":[103],"nuisance":[106],"be":[108],"eliminated,":[109],"innovatively":[111],"repurpose":[112],"Error":[116],"(LTE)":[117],"an":[119],"unsupervised":[120],"forward":[121],"inductive":[122],"bias.":[123],"By":[124],"mapping":[125],"LTE":[127],"into":[128],"dynamic":[130],"spatial":[131],"attention":[132],"mask,":[133],"our":[134,178],"architecture":[135],"gracefully":[136],"preserves":[137],"high-precision":[138],"ODE":[140],"evolution":[141],"stable":[143],"regions,":[144],"while":[145],"adaptively":[146],"triggering":[147],"discrete":[149],"compensation":[150],"branch":[151],"exclusively":[152],"shock":[154],"points.":[155],"Trained":[156],"purely":[157],"end-to-end":[158],"without":[159],"penalties,":[161],"LTE-ODE":[162],"achieves":[163],"state-of-the-art":[164],"performance":[165],"on":[166,180],"multiple":[167],"benchmarks,":[169],"exhibiting":[170],"exceptional":[171],"robustness":[172],"against":[173],"highly":[174],"non-linear":[175],"fluctuations.":[176],"Furthermore,":[177],"ablation":[179],"steps":[182],"demonstrates":[183],"high":[184],"deployment":[185],"flexibility,":[186],"allowing":[187],"seamlessly":[191],"adapt":[192],"varying":[194],"hardware":[195],"memory":[196],"real-world":[199],"applications.":[200]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-07T00:00:00"}