{"id":"https://openalex.org/W2742331464","doi":"https://doi.org/10.23919/icif.2017.8009680","title":"Score matching based assumed density filtering with the von Mises-Fisher distribution","display_name":"Score matching based assumed density filtering with the von Mises-Fisher distribution","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2742331464","doi":"https://doi.org/10.23919/icif.2017.8009680","mag":"2742331464"},"language":"en","primary_location":{"id":"doi:10.23919/icif.2017.8009680","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009680","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","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/A5067570380","display_name":"Mario Bukal","orcid":"https://orcid.org/0000-0003-3419-3894"},"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"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Mario Bukal","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, HR, Croatia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, HR, Croatia","institution_ids":["https://openalex.org/I181343428"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035622961","display_name":"Ivan Markovi\u0107","orcid":"https://orcid.org/0000-0003-4138-1113"},"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"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Ivan Markovic","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, HR, Croatia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, HR, Croatia","institution_ids":["https://openalex.org/I181343428"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001473761","display_name":"Ivan Petrovi\u0107","orcid":"https://orcid.org/0000-0001-9961-5627"},"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"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Ivan Petrovic","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, HR, Croatia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, HR, Croatia","institution_ids":["https://openalex.org/I181343428"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181343428"],"apc_list":null,"apc_paid":null,"fwci":0.6921,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74425393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.996999979019165,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9908999800682068,"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/von-mises-distribution","display_name":"von Mises distribution","score":0.7376013994216919},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6824268102645874},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.5797154903411865},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5329388380050659},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.44041919708251953},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.43900689482688904},{"id":"https://openalex.org/keywords/von-mises-yield-criterion","display_name":"von Mises yield criterion","score":0.40054234862327576},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3864558935165405},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38334301114082336},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.37212589383125305},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3258652985095978},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2971908152103424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29461538791656494},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.25456416606903076}],"concepts":[{"id":"https://openalex.org/C198138136","wikidata":"https://www.wikidata.org/wiki/Q7941490","display_name":"von Mises distribution","level":4,"score":0.7376013994216919},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6824268102645874},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.5797154903411865},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5329388380050659},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.44041919708251953},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.43900689482688904},{"id":"https://openalex.org/C155165730","wikidata":"https://www.wikidata.org/wiki/Q1319519","display_name":"von Mises yield criterion","level":3,"score":0.40054234862327576},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3864558935165405},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38334301114082336},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.37212589383125305},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3258652985095978},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2971908152103424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29461538791656494},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.25456416606903076},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icif.2017.8009680","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icif.2017.8009680","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 20th International Conference on Information Fusion (Fusion)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W982971517","https://openalex.org/W1488825527","https://openalex.org/W1505878979","https://openalex.org/W1506984070","https://openalex.org/W1585160083","https://openalex.org/W1672145121","https://openalex.org/W1964500941","https://openalex.org/W2011833091","https://openalex.org/W2014787937","https://openalex.org/W2030162913","https://openalex.org/W2031868281","https://openalex.org/W2035868186","https://openalex.org/W2044020847","https://openalex.org/W2060237968","https://openalex.org/W2068469907","https://openalex.org/W2105777181","https://openalex.org/W2106873007","https://openalex.org/W2131452167","https://openalex.org/W2137585588","https://openalex.org/W2141461755","https://openalex.org/W2145080288","https://openalex.org/W2150440166","https://openalex.org/W2156787958","https://openalex.org/W2222512263","https://openalex.org/W2295776707","https://openalex.org/W2518047326","https://openalex.org/W2771551607","https://openalex.org/W3004970274","https://openalex.org/W3016005719","https://openalex.org/W3102917240","https://openalex.org/W4246202668","https://openalex.org/W6630115253","https://openalex.org/W6679661745","https://openalex.org/W6726481539"],"related_works":["https://openalex.org/W2015913877","https://openalex.org/W2743399515","https://openalex.org/W2912327495","https://openalex.org/W2562263695","https://openalex.org/W2108205837","https://openalex.org/W2135187896","https://openalex.org/W4399440807","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2002927610"],"abstract_inverted_index":{"Bayesian":[0,109],"filters":[1,209],"are":[2],"often":[3],"used":[4,25],"in":[5,141],"statistical":[6],"inference":[7],"and":[8,17,131,205,212],"consist":[9],"of":[10,40,57,88,108,114,127,220],"recursively":[11],"alternating":[12],"between":[13],"two":[14],"steps:":[15],"prediction":[16,69],"correction.":[18],"Most":[19],"commonly":[20],"the":[21,27,38,41,45,50,61,68,102,106,115,125,128,137,142,145,152,162,167,172,195,203,225],"Gaussian":[22],"distribution":[23,48,130,154],"is":[24],"within":[26,105],"Bayes":[28],"filtering":[29,82,112],"framework,":[30],"but":[31,156,180],"other":[32,80],"distributions,":[33],"which":[34,140],"could":[35],"model":[36],"better":[37],"nature":[39],"estimated":[42],"phenomenon":[43],"like":[44],"von":[46,62,76],"Mises-Fisher":[47,63,77],"on":[49,216,224],"unit":[51,226],"sphere,":[52],"have":[53],"also":[54,150],"been":[55],"subject":[56],"research":[58],"interest.":[59],"However,":[60],"filter":[64],"requires":[65],"approximations":[66],"since":[67],"step":[70],"does":[71],"not":[72,189],"yield":[73],"an":[74],"another":[75],"distribution.":[78],"Furthermore,":[79],"advanced":[81],"methods":[83],"require":[84,190],"approximating":[85],"a":[86,92,217],"mixture":[87],"distributions":[89],"with":[90,136,177,181],"just":[91],"single":[93,211],"component.":[94],"In":[95,166,194],"this":[96],"paper":[97,168],"we":[98,169,197],"propose":[99],"to":[100],"use":[101],"score":[103,173,206],"matching":[104,121,133,149,174,207],"context":[107],"assumed":[110],"density":[111],"inlieu":[113],"more":[116],"common":[117],"moment":[118,186,204],"matching.":[119],"Moment":[120],"functions":[122],"by":[123,160,201],"assuming":[124],"type":[126],"resulting":[129,153],"then":[132],"its":[134],"moments":[135],"prior":[138],"distribution,":[139],"end":[143],"minimizes":[144],"Kullback-Leibler":[146],"divergence.":[147],"Score":[148],"assumes":[151],"type,":[155],"finds":[157],"optimal":[158],"parameters":[159],"minimizing":[161],"relative":[163],"Fisher":[164],"information.":[165],"show":[170],"that":[171],"procedure":[175],"results":[176,200],"identical":[178],"performance,":[179],"simpler":[182],"equations":[183],"that,":[184],"unlike":[185],"matching,":[187],"do":[188],"tedious":[191],"numerical":[192],"methods.":[193],"end,":[196],"corroborate":[198],"theoretical":[199],"running":[202],"based":[208],"for":[210],"multiple":[213],"object":[214],"tracking":[215],"large":[218],"number":[219],"randomly":[221],"generated":[222],"trajectories":[223],"sphere.":[227]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
