{"id":"https://openalex.org/W2396585558","doi":null,"title":"Assessing the perceived predictability of functions","display_name":"Assessing the perceived predictability of functions","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2396585558","mag":"2396585558"},"language":"en","primary_location":{"id":"pmh:oai:pure.mpg.de:item_3243357","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","pdf_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"37th Annual Meeting of the Cognitive Science Society (CogSci 2015): Mind, Technology and Society","raw_type":"info:eu-repo/semantics/conferenceObject"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101768980","display_name":"Eric Schulz","orcid":"https://orcid.org/0000-0003-3088-0371","observed_orcids":["https://orcid.org/0000-0003-3088-0371"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eric Schulz","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3088-0371","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071093940","display_name":"Joshua B. Tenenbaum","orcid":"https://orcid.org/0000-0002-1925-2035","observed_orcids":["https://orcid.org/0000-0002-1925-2035","https://orcid.org/0000-0002-0138-163X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joshua B. Tenenbaum","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-1925-2035","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006302473","display_name":"David N. Reshef","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David N. Reshef","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042858264","display_name":"Maarten Speekenbrink","orcid":"https://orcid.org/0000-0003-3221-1091","observed_orcids":["https://orcid.org/0000-0003-3221-1091"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maarten Speekenbrink","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3221-1091","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5031715686","display_name":"Samuel Joseph Gershman","orcid":"https://orcid.org/0000-0002-6546-3298","observed_orcids":["https://orcid.org/0000-0002-6546-3298"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel J. Gershman","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6546-3298","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6852,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.92859805,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2116","last_page":"2121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.8471999764442444,"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":0.8471999764442444,"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/T10427","display_name":"Visual perception and processing mechanisms","score":0.026599999517202377,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14394","display_name":"Cognitive Science and Education Research","score":0.018699999898672104,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perceived-predictability","display_name":"perceived predictability","score":0.9700000286102295},{"id":"https://openalex.org/keywords/gaussian-process-regression","display_name":"Gaussian process regression","score":0.8349999785423279},{"id":"https://openalex.org/keywords/learning-curve","display_name":"learning curve","score":0.9639999866485596},{"id":"https://openalex.org/keywords/smoothness-of-functions","display_name":"smoothness of functions","score":0.9589999914169312},{"id":"https://openalex.org/keywords/noise-variance","display_name":"noise variance","score":0.6019999980926514},{"id":"https://openalex.org/keywords/sample-size","display_name":"sample size","score":0.8960000276565552},{"id":"https://openalex.org/keywords/probabilistic-reasoning","display_name":"probabilistic reasoning","score":0.40700000524520874}],"concepts":[{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.9659993648529053},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.8475441932678223},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5545178055763245},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.543777346611023},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5383250713348389},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5196620225906372},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5175763368606567},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5148324370384216},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5032293200492859},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.4792218804359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4715423882007599},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4178960919380188},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3912253677845001},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3674165606498718},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.360862672328949},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.12867659330368042},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0977528989315033},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"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":3,"locations":[{"id":"pmh:oai:pure.mpg.de:item_3243357","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","pdf_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"37th Annual Meeting of the Cognitive Science Society (CogSci 2015): Mind, Technology and Society","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:escholarship.org:ark:/13030/qt0w17n1rw","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/0w17n1rw","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the Annual Meeting of the Cognitive Science Society, vol 37, iss 0","raw_type":"article"},{"id":"mag:2396585558","doi":null,"is_oa":false,"landing_page_url":"http://dblp.uni-trier.de/db/conf/cogsci/cogsci2015.html#SchulzTRSG15","pdf_url":null,"source":{"id":"https://openalex.org/S78735424","display_name":"Cognitive Science","issn_l":"0364-0213","issn":["0364-0213","1551-6709"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","dongbi-c","erih-plus","jufo-2","ki-jl-2","medline","norway-2","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Cognitive Science","raw_type":null}],"best_oa_location":{"id":"pmh:oai:pure.mpg.de:item_3243357","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","pdf_url":"http://hdl.handle.net/21.11116/0000-0006-B437-1","source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"37th Annual Meeting of the Cognitive Science Society (CogSci 2015): Mind, Technology and Society","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2396585558.pdf","grobid_xml":"https://content.openalex.org/works/W2396585558.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1597810135","https://openalex.org/W1598589417","https://openalex.org/W1746819321","https://openalex.org/W1975951781","https://openalex.org/W1976035906","https://openalex.org/W2000730906","https://openalex.org/W2020120284","https://openalex.org/W2024389111","https://openalex.org/W2043187947","https://openalex.org/W2069082406","https://openalex.org/W2079988037","https://openalex.org/W2089076337","https://openalex.org/W2125849100","https://openalex.org/W2142959074","https://openalex.org/W2158451137","https://openalex.org/W2158890446","https://openalex.org/W2166851712","https://openalex.org/W2486016413","https://openalex.org/W3099984476"],"related_works":["https://openalex.org/W1597810135","https://openalex.org/W3036871516","https://openalex.org/W7098878442","https://openalex.org/W1550642976","https://openalex.org/W2100538233","https://openalex.org/W2324413996","https://openalex.org/W6892717492","https://openalex.org/W2377627938","https://openalex.org/W4312815653","https://openalex.org/W203461737"],"abstract_inverted_index":{"How":[0],"do":[1],"we":[2,24,78],"perceive":[3],"the":[4,27,39,45,66,98,101],"predictability":[5,37],"of":[6,12,29,41],"functions?":[7],"We\\nderive":[8],"a":[9,13,30,91],"rational":[10],"measure":[11],"function's":[14],"predictabil-\\nity":[15,81],"based":[16],"on":[17,65],"Gaussian":[18,58],"process":[19,59],"learning":[20,76],"curves.":[21],"Using\\nthis":[22],"measure,":[23],"show":[25],"that":[26,105],"smoothness":[28],"func-\\ntion":[31],"can":[32,50,107],"be":[33,51,109],"more":[34],"important":[35],"to":[36],"judgments\\nthan":[38],"variance":[40,99],"additive":[42],"noise":[43],"or":[44],"number":[46],"of\\nsamples.":[47],"These":[48],"patterns":[49],"captured":[52],"well":[53],"by":[54],"the\\nlearning":[55],"curve":[56],"for":[57,94],"regression,":[60],"which":[61],"in\\nturn":[62],"crucially":[63],"depends":[64],"eigenvalue":[67],"spectrum":[68],"of\\nthe":[69],"covariance":[70],"function.":[71],"Using":[72],"approximate":[73],"bounds":[74],"on\\nthe":[75],"curve,":[77],"model":[79],"participants'":[80],"judgments":[82],"about":[83,112],"sampled":[84],"functions":[85,116],"and":[86,100],"?nd":[87],"that\\nsmoothness":[88],"is":[89],"indeed":[90],"better":[92],"predictor":[93],"perceived\\npredictability":[95],"than":[96],"both":[97],"sample\\nsize.":[102],"This":[103],"means":[104],"it":[106],"sometimes":[108],"preferable\\nto":[110],"learn":[111],"noisy":[113],"but":[114],"smooth":[115],"instead":[117],"of\\ndeterministic":[118],"complex":[119],"ones.":[120]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":5}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
