{"id":"https://openalex.org/W3048464360","doi":"https://doi.org/10.1109/lra.2020.3015449","title":"Heteroscedastic Uncertainty for Robust Generative Latent Dynamics","display_name":"Heteroscedastic Uncertainty for Robust Generative Latent Dynamics","publication_year":2020,"publication_date":"2020-08-11","ids":{"openalex":"https://openalex.org/W3048464360","doi":"https://doi.org/10.1109/lra.2020.3015449","mag":"3048464360"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2020.3015449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2020.3015449","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.08157","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Oliver Limoyo","orcid":"https://orcid.org/0000-0001-6886-2633"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Oliver Limoyo","raw_affiliation_strings":["Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0001-6886-2633","affiliations":[{"raw_affiliation_string":"Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bryan Chan","orcid":"https://orcid.org/0000-0002-6278-9575"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bryan Chan","raw_affiliation_strings":["Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0002-6278-9575","affiliations":[{"raw_affiliation_string":"Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Filip Maric","orcid":"https://orcid.org/0000-0002-4171-8006"},"institutions":[{"id":"https://openalex.org/I181343428","display_name":"University of Zagreb","ror":"https://ror.org/00mv6sv71","country_code":"HR","type":"education","lineage":["https://openalex.org/I181343428"]},{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA","HR"],"is_corresponding":false,"raw_author_name":"Filip Maric","raw_affiliation_strings":["Laboratory for Autonomous Systems, and Mobile Robotics (LAMOR), University of Zagreb, Zagreb, Croatia","Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4171-8006","affiliations":[{"raw_affiliation_string":"Laboratory for Autonomous Systems, and Mobile Robotics (LAMOR), University of Zagreb, Zagreb, Croatia","institution_ids":["https://openalex.org/I181343428"]},{"raw_affiliation_string":"Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Brandon Wagstaff","orcid":"https://orcid.org/0000-0001-7808-0045"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Brandon Wagstaff","raw_affiliation_strings":["Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7808-0045","affiliations":[{"raw_affiliation_string":"Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":null,"display_name":"A. Rupam Mahmood","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"A. Rupam Mahmood","raw_affiliation_strings":["Reinforcement Learning, and Artificial Intelligence Laboratory (RLAI), University of Alberta, Edmonton, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Reinforcement Learning, and Artificial Intelligence Laboratory (RLAI), University of Alberta, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jonathan Kelly","orcid":"https://orcid.org/0000-0002-5528-6136"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jonathan Kelly","raw_affiliation_strings":["Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5528-6136","affiliations":[{"raw_affiliation_string":"Space, and Terrestrial Autonomous Robotic Systems (STARS) Laboratory, University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4895,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.66081417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"5","issue":"4","first_page":"6654","last_page":"6661"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.24619999527931213,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.24619999527931213,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.24379999935626984,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.23770000040531158,"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/generative-model","display_name":"Generative model","score":0.5353999733924866},{"id":"https://openalex.org/keywords/heteroscedasticity","display_name":"Heteroscedasticity","score":0.5052000284194946},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4999000132083893},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44200000166893005},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.44110000133514404},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.42149999737739563},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4018999934196472},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.36079999804496765},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3483000099658966}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5898000001907349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5365999937057495},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5353999733924866},{"id":"https://openalex.org/C101104100","wikidata":"https://www.wikidata.org/wiki/Q1063540","display_name":"Heteroscedasticity","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4999000132083893},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44200000166893005},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.44110000133514404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43709999322891235},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.30329999327659607},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C176248197","wikidata":"https://www.wikidata.org/wiki/Q458526","display_name":"Probably approximately correct learning","level":4,"score":0.2928999960422516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29159998893737793},{"id":"https://openalex.org/C104409967","wikidata":"https://www.wikidata.org/wiki/Q1054836","display_name":"Homoscedasticity","level":3,"score":0.2838999927043915},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.26170000433921814},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2020.3015449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2020.3015449","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2008.08157","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08157","pdf_url":"https://arxiv.org/pdf/2008.08157","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.08157","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.08157","pdf_url":"https://arxiv.org/pdf/2008.08157","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320994","display_name":"Canada Research Chairs","ror":"https://ror.org/0517h6h17"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1516111018","https://openalex.org/W1957496711","https://openalex.org/W2094227853","https://openalex.org/W2097412577","https://openalex.org/W2102716594","https://openalex.org/W2105934661","https://openalex.org/W2164522996","https://openalex.org/W2165901038","https://openalex.org/W2734960757","https://openalex.org/W2899160681","https://openalex.org/W2963806976","https://openalex.org/W2964199361","https://openalex.org/W4231367092","https://openalex.org/W4240338048","https://openalex.org/W4244577065","https://openalex.org/W6609413351","https://openalex.org/W6617145748","https://openalex.org/W6617744952","https://openalex.org/W6623316541","https://openalex.org/W6637967152","https://openalex.org/W6638058698","https://openalex.org/W6639118987","https://openalex.org/W6639732818","https://openalex.org/W6640963894","https://openalex.org/W6680657880","https://openalex.org/W6696497002","https://openalex.org/W6711952718","https://openalex.org/W6712730493","https://openalex.org/W6719357382","https://openalex.org/W6728354068","https://openalex.org/W6730042731","https://openalex.org/W6744063608","https://openalex.org/W6745638589","https://openalex.org/W6754162236","https://openalex.org/W6754184789","https://openalex.org/W6754615820","https://openalex.org/W6756256016","https://openalex.org/W6780559895"],"related_works":[],"abstract_inverted_index":{"Learning":[0],"or":[1,132,141],"identifying":[2],"dynamics":[3,46,54,101],"from":[4,28,148],"a":[5,11,29,40,72,89,94,128,157,163,186],"sequence":[6],"of":[7,74,130,196,199],"high-dimensional":[8,35],"observations":[9,36],"is":[10,103,124],"difficult":[12,113],"challenge":[13],"in":[14,43,193],"many":[15],"domains,":[16],"including":[17],"reinforcement":[18],"learning,":[19],"and":[20,77,98,108,150,162,179],"control.":[21],"The":[22],"problem":[23],"has":[24],"recently":[25],"been":[26,59],"studied":[27],"generative":[30],"perspective":[31],"through":[32],"latent":[33,53,95],"dynamics:":[34],"are":[37],"embedded":[38],"into":[39],"lower-dimensional":[41],"space":[42],"which":[44],"the":[45,99,194],"can":[47],"be":[48,69],"learned.":[49],"Despite":[50],"some":[51],"successes,":[52],"models":[55],"have":[56],"not":[57,80],"yet":[58],"applied":[60],"to":[61,71,91,126,185],"real-world":[62,164],"robotic":[63,165],"systems":[64],"where":[65],"learned":[66],"representations":[67],"must":[68],"robust":[70],"variety":[73],"perceptual":[75],"confounds,":[76],"noise":[78],"sources":[79],"seen":[81],"during":[82],"training.":[83],"In":[84],"this":[85],"letter,":[86],"we":[87,119],"present":[88,146],"method":[90],"jointly":[92],"learn":[93],"state":[96],"representation,":[97],"associated":[100],"that":[102,171,188],"amenable":[104],"for":[105],"long-term":[106],"planning,":[107],"closed-loop":[109],"control":[110,151,182],"under":[111],"perceptually":[112],"conditions.":[114],"As":[115],"our":[116,122,172],"main":[117],"contribution,":[118],"describe":[120],"how":[121],"representation":[123],"able":[125],"capture":[127],"notion":[129],"heteroscedastic":[131],"input-specific":[133],"uncertainty":[134,191],"at":[135],"test":[136],"time":[137],"by":[138],"detecting":[139],"novel":[140],"out-of-distribution":[142],"(OOD)":[143],"inputs.":[144],"We":[145,169],"results":[147],"prediction,":[149],"experiments":[152],"on":[153],"two":[154],"image-based":[155],"tasks:":[156],"simulated":[158],"pendulum":[159],"balancing":[160],"task,":[161],"manipulator":[166],"reaching":[167],"task.":[168],"demonstrate":[170],"model":[173,187],"produces":[174],"significantly":[175],"more":[176],"accurate":[177],"predictions,":[178],"exhibits":[180],"improved":[181],"performance,":[183],"compared":[184],"assumes":[189],"homoscedastic":[190],"only,":[192],"presence":[195],"varying":[197],"degrees":[198],"input":[200],"degradation.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2020-08-18T00:00:00"}