乐胖代购免代理版

{"id":"https://openalex.org/W3174147249","doi":"https://doi.org/10.1609/aaai.v35i7.16764","title":"Differentiable Fluids with Solid Coupling for Learning and Control","display_name":"Differentiable Fluids with Solid Coupling for Learning and Control","publication_year":2021,"publication_date":"2021-05-18","ids":{"openalex":"https://openalex.org/W3174147249","doi":"https://doi.org/10.1609/aaai.v35i7.16764","mag":"3174147249"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v35i7.16764","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/16764/16571","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/16764/16571","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081056035","display_name":"Tetsuya Takahashi","orcid":"https://orcid.org/0000-0002-2917-1810"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]},{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tetsuya Takahashi","raw_affiliation_strings":["Adobe\nUniversity of Maryland at College Park"],"affiliations":[{"raw_affiliation_string":"Adobe\nUniversity of Maryland at College Park","institution_ids":["https://openalex.org/I1306409833","https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101466877","display_name":"Junbang Liang","orcid":"https://orcid.org/0000-0001-7114-9847"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junbang Liang","raw_affiliation_strings":["University of Maryland at College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland at College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010354503","display_name":"Yi-Ling Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Ling Qiao","raw_affiliation_strings":["University of Maryland at College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland at College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102878981","display_name":"Ming C. Lin","orcid":"https://orcid.org/0000-0003-3736-6949"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming C. Lin","raw_affiliation_strings":["University of Maryland at College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland at College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.509,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.998302,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":91},"biblio":{"volume":"35","issue":"7","first_page":"6138","last_page":"6146"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9999,"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":0.9999,"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/T11751","display_name":"Lattice Boltzmann Simulation Studies","score":0.9934,"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/T10360","display_name":"Fluid Dynamics and Turbulent Flows","score":0.9813,"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"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.68697906},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.6600906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6317698},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6277333},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5339704},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5258989},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49792504},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.44375202},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.4271643},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4159116},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.41174296},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36054426},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.32401624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24277833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2335358},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18929124},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1812912},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12940973},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.10193959},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.087145865}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v35i7.16764","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/16764/16571","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v35i7.16764","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/16764/16571","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":62,"referenced_works":["https://openalex.org/W1605438009","https://openalex.org/W2046090405","https://openalex.org/W2067910404","https://openalex.org/W2089858332","https://openalex.org/W2145366562","https://openalex.org/W2295821368","https://openalex.org/W2384495648","https://openalex.org/W2501995758","https://openalex.org/W2515505748","https://openalex.org/W2534240011","https://openalex.org/W2556096037","https://openalex.org/W2605917215","https://openalex.org/W2736601468","https://openalex.org/W2787774738","https://openalex.org/W2804632314","https://openalex.org/W2805516822","https://openalex.org/W2805883505","https://openalex.org/W2807201937","https://openalex.org/W2811105005","https://openalex.org/W2811435282","https://openalex.org/W2891122218","https://openalex.org/W2895524695","https://openalex.org/W2906744519","https://openalex.org/W2945704673","https://openalex.org/W2951660942","https://openalex.org/W2962977755","https://openalex.org/W2963030758","https://openalex.org/W2963504959","https://openalex.org/W2963942037","https://openalex.org/W2963970238","https://openalex.org/W2964128214","https://openalex.org/W2965742591","https://openalex.org/W2968042644","https://openalex.org/W2970529185","https://openalex.org/W2970971581","https://openalex.org/W2978940263","https://openalex.org/W2985630280","https://openalex.org/W2995001833","https://openalex.org/W2995253198","https://openalex.org/W2996324165","https://openalex.org/W3003038987","https://openalex.org/W3007913393","https://openalex.org/W3021900716","https://openalex.org/W3034237986","https://openalex.org/W3035431334","https://openalex.org/W3035580435","https://openalex.org/W3038186741","https://openalex.org/W3038540964","https://openalex.org/W3038570409","https://openalex.org/W3102140816","https://openalex.org/W3104397553","https://openalex.org/W3107819465","https://openalex.org/W3109952375","https://openalex.org/W3125460488","https://openalex.org/W4212774754","https://openalex.org/W4246185210","https://openalex.org/W4251259970","https://openalex.org/W4287556695","https://openalex.org/W4294563757","https://openalex.org/W4295312788","https://openalex.org/W4301496368","https://openalex.org/W4361733989"],"related_works":["https://openalex.org/W4362501864","https://openalex.org/W4327738859","https://openalex.org/W4306904969","https://openalex.org/W4285277090","https://openalex.org/W3181683615","https://openalex.org/W2348722996","https://openalex.org/W2334570605","https://openalex.org/W1980454230","https://openalex.org/W1633485514","https://openalex.org/W1604739066"],"abstract_inverted_index":{"We":[0,80],"introduce":[1],"an":[2],"efficient":[3],"differentiable":[4],"fluid":[5,73],"simulator":[6,58],"that":[7,44],"can":[8],"be":[9],"integrated":[10],"with":[11,37,54,75,95],"deep":[12],"neural":[13],"networks":[14],"as":[15],"a":[16,41],"part":[17],"of":[18,35,72,84,119],"layers":[19],"for":[20,68,87],"learning":[21,112],"dynamics":[22],"and":[23,90,109],"solving":[24,88],"control":[25,91],"problems.":[26],"It":[27],"offers":[28],"the":[29,51,60,66,82,102],"capability":[30],"to":[31,63],"handle":[32],"one-way":[33,96],"coupling":[34],"fluids":[36,94],"rigid":[38],"objects":[39],"using":[40],"variational":[42],"principle":[43],"naturally":[45],"enforces":[46],"necessary":[47],"boundary":[48],"conditions":[49],"at":[50,115],"fluid-solid":[52],"interface":[53],"sub-grid":[55],"details.":[56],"This":[57],"utilizes":[59],"adjoint":[61],"method":[62,86,100],"efficiently":[64],"compute":[65],"gradient":[67,104],"multiple":[69],"time":[70],"steps":[71],"simulation":[74],"user":[76],"defined":[77],"objective":[78],"functions.":[79],"demonstrate":[81],"effectiveness":[83],"our":[85],"inverse":[89],"problems":[92],"on":[93],"coupled":[97],"solids.":[98],"Our":[99],"outperforms":[101],"previous":[103],"computations,":[105],"state-of-the-art":[106],"derivative-free":[107],"optimization,":[108],"model-free":[110],"reinforcement":[111],"techniques":[113],"by":[114],"least":[116],"one":[117],"order":[118],"magnitude.":[120]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3174147249","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2024-12-13T11:05:56.148871","created_date":"2021-07-05"}