{"id":"https://openalex.org/W2012071615","doi":"https://doi.org/10.1109/igarss.2015.7325685","title":"Biophysical parameter retrieval with warped Gaussian processes","display_name":"Biophysical parameter retrieval with warped Gaussian processes","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2012071615","doi":"https://doi.org/10.1109/igarss.2015.7325685","mag":"2012071615"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2015.7325685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7325685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5085480844","display_name":"Jordi Mu\u00f1oz-Mar\u0131\u0301","orcid":"https://orcid.org/0000-0002-3014-3921"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jordi Munoz-Mari","raw_affiliation_strings":["Universitat de Val\u00e8ncia, Image Processing Lab (IPL), Val\u00e8ncia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Val\u00e8ncia, Image Processing Lab (IPL), Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079448372","display_name":"Jochem Verrelst","orcid":"https://orcid.org/0000-0002-6313-2081"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jochem Verrelst","raw_affiliation_strings":["Universitat de Valencia, Valencia, Comunitat Valenciana, ES","Universitat de Val\u00e8ncia, Image Processing Lab (IPL), Val\u00e8ncia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Valencia, Valencia, Comunitat Valenciana, ES","institution_ids":["https://openalex.org/I16097986"]},{"raw_affiliation_string":"Universitat de Val\u00e8ncia, Image Processing Lab (IPL), Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076182014","display_name":"Miguel L\u00e1zaro-Gredilla","orcid":"https://orcid.org/0000-0002-4528-5084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miguel Lazaro-Gredilla","raw_affiliation_strings":["Vicarious.com, San Francisco, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vicarious.com, San Francisco, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108083011","display_name":"Gustau Camps-Vails","orcid":null},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Gustau Camps-Vails","raw_affiliation_strings":["Universitat de Valencia, Valencia, Comunitat Valenciana, ES","Universitat de Val\u00e8ncia, Image Processing Lab (IPL), Val\u00e8ncia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitat de Valencia, Valencia, Comunitat Valenciana, ES","institution_ids":["https://openalex.org/I16097986"]},{"raw_affiliation_string":"Universitat de Val\u00e8ncia, Image Processing Lab (IPL), Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I16097986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"13","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9656000137329102,"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":0.9656000137329102,"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/heteroscedasticity","display_name":"Heteroscedasticity","score":0.7369502186775208},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6489701271057129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5893194079399109},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5531687140464783},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.5412866473197937},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.49072229862213135},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.4673108756542206},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4619280695915222},{"id":"https://openalex.org/keywords/data-transformation","display_name":"Data transformation","score":0.459760844707489},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.42683202028274536},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.42323336005210876},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.39796239137649536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.390980988740921},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3843176066875458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34749776124954224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.26148098707199097},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.252143919467926},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19325542449951172}],"concepts":[{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.7369502186775208},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6489701271057129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5893194079399109},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5531687140464783},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.5412866473197937},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.49072229862213135},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.4673108756542206},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4619280695915222},{"id":"https://openalex.org/C150670458","wikidata":"https://www.wikidata.org/wiki/Q4272815","display_name":"Data transformation","level":3,"score":0.459760844707489},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.42683202028274536},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.42323336005210876},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.39796239137649536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.390980988740921},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3843176066875458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34749776124954224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26148098707199097},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.252143919467926},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19325542449951172},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C135572916","wikidata":"https://www.wikidata.org/wiki/Q193351","display_name":"Data warehouse","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2015.7325685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7325685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1746819321","https://openalex.org/W1987607942","https://openalex.org/W1988510559","https://openalex.org/W2003339231","https://openalex.org/W2007101051","https://openalex.org/W2007342648","https://openalex.org/W2017117437","https://openalex.org/W2045331152","https://openalex.org/W2130670721","https://openalex.org/W2134477639","https://openalex.org/W2137512539","https://openalex.org/W2142959074","https://openalex.org/W2160215259","https://openalex.org/W2167881994","https://openalex.org/W2171305756","https://openalex.org/W2951308445","https://openalex.org/W2951675424","https://openalex.org/W4211049957","https://openalex.org/W4285719527","https://openalex.org/W6680216138","https://openalex.org/W6680220816","https://openalex.org/W6681609451"],"related_works":["https://openalex.org/W1676609285","https://openalex.org/W3148934225","https://openalex.org/W2351648145","https://openalex.org/W2038165226","https://openalex.org/W2052845382","https://openalex.org/W4254549582","https://openalex.org/W2148483050","https://openalex.org/W3124109721","https://openalex.org/W2916152223","https://openalex.org/W2356241365"],"abstract_inverted_index":{"This":[0,31],"paper":[1],"focuses":[2],"on":[3,8],"biophysical":[4],"parameter":[5],"retrieval":[6],"based":[7],"Gaussian":[9],"Processes":[10],"(GPs).":[11],"Very":[12],"often":[13],"an":[14],"arbitrary":[15],"transformation":[16,69,90],"is":[17],"applied":[18],"to":[19,26,36,59],"the":[20,29,38,46,48,51,67,72,109,113,117,125],"observed":[21],"variable":[22],"(e.g.":[23],"chlorophyll":[24,121],"content)":[25],"better":[27],"pose":[28],"problem.":[30],"standard":[32,104],"practice":[33],"essentially":[34],"tries":[35],"linearize/uniformize":[37],"distribution":[39],"by":[40],"applying":[41],"non-linear":[42],"link":[43],"functions":[44],"like":[45],"logarithmic,":[47],"exponential":[49],"or":[50],"logistic":[52],"functions.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"propose":[58],"use":[60],"a":[61,87,92,129],"GP":[62,77],"model":[63,99,115],"that":[64],"automatically":[65],"learns":[66],"optimal":[68],"directly":[70],"from":[71],"data.":[73],"The":[74,94],"so-called":[75],"warped":[76],"regression":[78],"(WGPR)":[79],"presented":[80],"in":[81],"[1]":[82],"models":[83],"output":[84],"observations":[85],"as":[86],"parametric":[88],"nonlinear":[89],"of":[91,96,112,119],"GP.":[93],"parameters":[95],"such":[97],"prior":[98],"are":[100],"then":[101],"learned":[102],"via":[103],"maximum":[105],"likelihood.":[106],"We":[107],"show":[108],"good":[110],"performance":[111],"proposed":[114],"for":[116],"estimation":[118],"oceanic":[120],"content,":[122],"which":[123],"outperforms":[124],"regular":[126],"GPR":[127,133],"and":[128],"more":[130],"advanced":[131],"heteroscedastic":[132],"model.":[134]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}