{"id":"https://openalex.org/W2551943286","doi":"https://doi.org/10.1109/mlsp.2016.7738855","title":"Scalable transformed additive signal decomposition by non-conjugate Gaussian process inference","display_name":"Scalable transformed additive signal decomposition by non-conjugate Gaussian process inference","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2551943286","doi":"https://doi.org/10.1109/mlsp.2016.7738855","mag":"2551943286"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/1544039/1/Sahani_adam-etal-2016-mlsp.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012976739","display_name":"Vincent Adam","orcid":"https://orcid.org/0000-0002-9953-3434"},"institutions":[{"id":"https://openalex.org/I4210115172","display_name":"Oxford Centre for Computational Neuroscience","ror":"https://ror.org/026ejyb70","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210115172"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Vincent Adam","raw_affiliation_strings":["Gatsby Computational Neuroscience Unit, University College London, London"],"affiliations":[{"raw_affiliation_string":"Gatsby Computational Neuroscience Unit, University College London, London","institution_ids":["https://openalex.org/I4210115172","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085437275","display_name":"James Hensman","orcid":"https://orcid.org/0000-0002-4989-3589"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Hensman","raw_affiliation_strings":["Faculty of Health and Medicine, Lancaster University CHICAS, Lancaster"],"affiliations":[{"raw_affiliation_string":"Faculty of Health and Medicine, Lancaster University CHICAS, Lancaster","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035341421","display_name":"Maneesh Sahani","orcid":"https://orcid.org/0000-0001-5560-3341"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]},{"id":"https://openalex.org/I4210115172","display_name":"Oxford Centre for Computational Neuroscience","ror":"https://ror.org/026ejyb70","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210115172"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maneesh Sahani","raw_affiliation_strings":["Gatsby Computational Neuroscience Unit, University College London, London"],"affiliations":[{"raw_affiliation_string":"Gatsby Computational Neuroscience Unit, University College London, London","institution_ids":["https://openalex.org/I4210115172","https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012976739"],"corresponding_institution_ids":["https://openalex.org/I4210115172","https://openalex.org/I45129253"],"apc_list":null,"apc_paid":null,"fwci":4.4341,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.95163682,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998000264167786,"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":0.9998000264167786,"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/T11236","display_name":"Control Systems and Identification","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9807000160217285,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.6724820733070374},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6100424528121948},{"id":"https://openalex.org/keywords/underdetermined-system","display_name":"Underdetermined system","score":0.5735116004943848},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5347432494163513},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.511382520198822},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47784802317619324},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4470656216144562},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34500011801719666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3331974148750305},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3239327073097229}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6724820733070374},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6100424528121948},{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.5735116004943848},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5347432494163513},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.511382520198822},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47784802317619324},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4470656216144562},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34500011801719666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3331974148750305},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3239327073097229},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mlsp.2016.7738855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738855","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1544039","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/1544039/","pdf_url":"https://discovery.ucl.ac.uk/1544039/1/Sahani_adam-etal-2016-mlsp.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:  Proceedings of MLSP2016.    IEEE (2016)     ","raw_type":"Proceedings paper"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1544039","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/1544039/","pdf_url":"https://discovery.ucl.ac.uk/1544039/1/Sahani_adam-etal-2016-mlsp.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:  Proceedings of MLSP2016.    IEEE (2016)     ","raw_type":"Proceedings paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2551943286.pdf","grobid_xml":"https://content.openalex.org/works/W2551943286.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W137285897","https://openalex.org/W215707797","https://openalex.org/W336602872","https://openalex.org/W1066208909","https://openalex.org/W1533660737","https://openalex.org/W1556631438","https://openalex.org/W1571870753","https://openalex.org/W1590505064","https://openalex.org/W1777124189","https://openalex.org/W1993631132","https://openalex.org/W2036084078","https://openalex.org/W2056958800","https://openalex.org/W2119047368","https://openalex.org/W2130283669","https://openalex.org/W2149273154","https://openalex.org/W2152829788","https://openalex.org/W2157826563","https://openalex.org/W2797583072","https://openalex.org/W2962731272","https://openalex.org/W2962833467","https://openalex.org/W3099618244","https://openalex.org/W4211049957","https://openalex.org/W4249303080","https://openalex.org/W4298870098","https://openalex.org/W6605566567","https://openalex.org/W6611576299","https://openalex.org/W6631732945","https://openalex.org/W6635315505","https://openalex.org/W6637968757","https://openalex.org/W6665073576","https://openalex.org/W6679226052","https://openalex.org/W6683442033","https://openalex.org/W6703654938","https://openalex.org/W7074235811"],"related_works":["https://openalex.org/W176802781","https://openalex.org/W2997320962","https://openalex.org/W4287906532","https://openalex.org/W3011121006","https://openalex.org/W2066796569","https://openalex.org/W3213509687","https://openalex.org/W121937048","https://openalex.org/W2375962929","https://openalex.org/W2169866437","https://openalex.org/W1964286703"],"abstract_inverted_index":{"Many":[0],"functions":[1],"and":[2,18,34,54,88],"signals":[3],"of":[4,11,45,79],"interest":[5],"are":[6],"formed":[7],"by":[8,20],"the":[9,27,46,66,80,98],"addition":[10],"multiple":[12],"underlying":[13,47],"components,":[14],"often":[15,50],"nonlinearly":[16],"transformed":[17],"modified":[19],"noise.":[21],"Examples":[22],"may":[23],"be":[24],"found":[25],"in":[26,114],"literature":[28],"on":[29,52],"Generalized":[30],"Additive":[31],"Models":[32],"[1]":[33],"Underdetermined":[35],"Source":[36],"Separation":[37],"[2]":[38],"or":[39],"other":[40],"mode":[41],"decomposition":[42],"techniques.":[43],"Recovery":[44],"component":[48],"processes":[49],"depends":[51],"finding":[53],"exploiting":[55],"statistical":[56,71],"regularities":[57],"within":[58],"them.":[59],"Gaussian":[60],"Processes":[61],"(GPs)":[62],"[3]":[63],"have":[64],"become":[65],"dominant":[67],"way":[68],"to":[69,97],"model":[70],"expectations":[72],"over":[73,110],"functions.":[74],"Recent":[75],"advances":[76],"make":[77],"inference":[78,109],"GP":[81,100],"posterior":[82,108],"efficient":[83],"for":[84],"large":[85],"scale":[86],"datasets":[87],"arbitrary":[89],"likelihoods":[90],"[4,5].":[91],"Here":[92],"we":[93],"extend":[94],"these":[95],"methods":[96],"additive":[99],"case":[101],"[6,":[102],"7],":[103],"thus":[104],"achieving":[105],"scalable":[106],"marginal":[107],"each":[111],"latent":[112],"function":[113],"settings":[115],"such":[116],"as":[117],"those":[118],"above.":[119]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
