{"id":"https://openalex.org/W4413394816","doi":"https://doi.org/10.23919/acc63710.2025.11107496","title":"Gaussian Processes with Noisy Regression Inputs for Dynamical Systems","display_name":"Gaussian Processes with Noisy Regression Inputs for Dynamical Systems","publication_year":2025,"publication_date":"2025-07-08","ids":{"openalex":"https://openalex.org/W4413394816","doi":"https://doi.org/10.23919/acc63710.2025.11107496"},"language":"en","primary_location":{"id":"doi:10.23919/acc63710.2025.11107496","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc63710.2025.11107496","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 American Control Conference (ACC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018655003","display_name":"Tobias M. Wolff","orcid":"https://orcid.org/0000-0002-2714-4296"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tobias M. Wolff","raw_affiliation_strings":["Leibniz University Hannover,Institute of Automatic Control,Hannover,Germany,30167"],"affiliations":[{"raw_affiliation_string":"Leibniz University Hannover,Institute of Automatic Control,Hannover,Germany,30167","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059736491","display_name":"Victor G. Lopez","orcid":"https://orcid.org/0000-0003-3989-4091"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Victor G. Lopez","raw_affiliation_strings":["Leibniz University Hannover,Institute of Automatic Control,Hannover,Germany,30167"],"affiliations":[{"raw_affiliation_string":"Leibniz University Hannover,Institute of Automatic Control,Hannover,Germany,30167","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057092836","display_name":"Matthias A. M\u00fcller","orcid":"https://orcid.org/0000-0002-4911-9526"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias A. M\u00fcller","raw_affiliation_strings":["Leibniz University Hannover,Institute of Automatic Control,Hannover,Germany,30167"],"affiliations":[{"raw_affiliation_string":"Leibniz University Hannover,Institute of Automatic Control,Hannover,Germany,30167","institution_ids":["https://openalex.org/I114112103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018655003"],"corresponding_institution_ids":["https://openalex.org/I114112103"],"apc_list":null,"apc_paid":null,"fwci":2.8414,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92448671,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"160","last_page":"165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9754999876022339,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9754999876022339,"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/computer-science","display_name":"Computer science","score":0.6415784955024719},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5794914960861206},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5458342432975769},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.48939505219459534},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46895426511764526},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4452993869781494},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3360975980758667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3349517583847046},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2725597321987152},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2350483536720276},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06320944428443909}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6415784955024719},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5794914960861206},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5458342432975769},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.48939505219459534},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46895426511764526},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4452993869781494},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3360975980758667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3349517583847046},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2725597321987152},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2350483536720276},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06320944428443909},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc63710.2025.11107496","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc63710.2025.11107496","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334678","display_name":"European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2007692097","https://openalex.org/W2091565802","https://openalex.org/W2149764047","https://openalex.org/W2163783967","https://openalex.org/W2619551236","https://openalex.org/W2808816909","https://openalex.org/W3119715644","https://openalex.org/W3183304118","https://openalex.org/W4206212643","https://openalex.org/W4211049957","https://openalex.org/W4411336492"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W4406204722","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2],"centered":[3],"around":[4],"the":[5,43,55,61,73,76,93],"approximation":[6],"of":[7,12,19,33,54,95],"dynamical":[8],"systems":[9,21],"by":[10,50,98],"means":[11],"Gaussian":[13,82],"processes.":[14],"To":[15],"this":[16,65],"end,":[17],"trajectories":[18,35],"such":[20],"must":[22],"be":[23,26],"collected":[24],"to":[25,70,85,101],"used":[27],"as":[28],"training":[29],"data.":[30],"The":[31],"measurements":[32],"these":[34],"are":[36,48],"typically":[37],"noisy,":[38],"which":[39],"implies":[40],"that":[41],"both":[42],"regression":[44,62,77],"inputs":[45,78],"and":[46,88],"outputs":[47],"corrupted":[49],"noise.":[51],"However,":[52],"most":[53],"literature":[56],"considers":[57],"only":[58],"noise":[59,74],"in":[60,75,79,105],"outputs.":[63],"In":[64],"paper,":[66],"we":[67],"show":[68],"how":[69],"account":[71],"for":[72],"an":[80],"extended":[81],"process":[83],"framework":[84,97],"approximate":[86],"scalar":[87],"multidimensional":[89],"systems.":[90],"We":[91],"demonstrate":[92],"potential":[94],"our":[96],"comparing":[99],"it":[100],"different":[102],"state-of-the-art":[103],"methods":[104],"several":[106],"simulation":[107],"examples.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}