{"id":"https://openalex.org/W197196944","doi":null,"title":"Filtering with Abstract Particles","display_name":"Filtering with Abstract Particles","publication_year":2014,"publication_date":"2014-06-21","ids":{"openalex":"https://openalex.org/W197196944","mag":"197196944"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.650.4663","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.4663","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.stanford.edu/~jsteinhardt/publications/abstract-filtering/paper.pdf","raw_type":"text"},"volume":null,"type":"article","indexed_in":[],"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/A5060196069","display_name":"Jacob Steinhardt","orcid":"https://orcid.org/0000-0002-0257-3860","observed_orcids":["https://orcid.org/0000-0002-0257-3860"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob Steinhardt","raw_affiliation_strings":["Stanford University, 353 Serra Street, Stanford, CA 94305 USA"],"raw_orcid":"https://orcid.org/0000-0002-0257-3860","affiliations":[{"raw_affiliation_string":"Stanford University, 353 Serra Street, Stanford, CA 94305 USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025255782","display_name":"Percy Liang","orcid":"https://orcid.org/0000-0002-0458-6139","observed_orcids":["https://orcid.org/0000-0002-0458-6139"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Percy Liang","raw_affiliation_strings":["Stanford University, 353 Serra Street, Stanford, CA 94305 USA"],"raw_orcid":"https://orcid.org/0000-0002-0458-6139","affiliations":[{"raw_affiliation_string":"Stanford University, 353 Serra Street, Stanford, CA 94305 USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":2.3257,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88802495,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"727","last_page":"735"},"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":0.9696999788284302,"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":0.9696999788284302,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.019099999219179153,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.002400000113993883,"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/filtering","display_name":"filtering","score":0.5339999794960022},{"id":"https://openalex.org/keywords/discrete-state-space","display_name":"discrete state space","score":0.8259999752044678},{"id":"https://openalex.org/keywords/hierarchical-decomposition","display_name":"hierarchical decomposition","score":0.8529999852180481},{"id":"https://openalex.org/keywords/particle-methods","display_name":"particle methods","score":0.44200000166893005},{"id":"https://openalex.org/keywords/beam-search","display_name":"beam search","score":0.8090000152587891},{"id":"https://openalex.org/keywords/sequential-monte-carlo","display_name":"sequential Monte Carlo","score":0.9929999709129333},{"id":"https://openalex.org/keywords/textual-reconstruction","display_name":"textual reconstruction","score":0.8790000081062317},{"id":"https://openalex.org/keywords/multiple-object-tracking","display_name":"multiple object tracking","score":0.9879999756813049}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7767602205276489},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.7220927476882935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7113155126571655},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.697022557258606},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.6077452301979065},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6058484315872192},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5644963979721069},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49619752168655396},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.47319647669792175},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4627388119697571},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.46155592799186707},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.435418039560318},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36673370003700256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.352692186832428},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.207932710647583},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08220246434211731},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.07106965780258179},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.650.4663","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.4663","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.stanford.edu/~jsteinhardt/publications/abstract-filtering/paper.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.960.1163","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.960.1163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://jmlr.org/proceedings/papers/v32/steinhardt14.pdf","raw_type":"text"},{"id":"mag:197196944","doi":null,"is_oa":false,"landing_page_url":"http://proceedings.mlr.press/v32/steinhardt14.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W92274471","https://openalex.org/W1516111018","https://openalex.org/W1593824711","https://openalex.org/W1606508130","https://openalex.org/W1934021597","https://openalex.org/W1934041838","https://openalex.org/W1944260052","https://openalex.org/W2034416530","https://openalex.org/W2041614298","https://openalex.org/W2055936398","https://openalex.org/W2092271904","https://openalex.org/W2099960657","https://openalex.org/W2107674477","https://openalex.org/W2111787305","https://openalex.org/W2117287544","https://openalex.org/W2128999403","https://openalex.org/W2135002837","https://openalex.org/W2139193890","https://openalex.org/W2139621418","https://openalex.org/W2151084831","https://openalex.org/W2152966212","https://openalex.org/W2160215259","https://openalex.org/W2160842254","https://openalex.org/W2161002933","https://openalex.org/W2168634963","https://openalex.org/W2171318693","https://openalex.org/W2180101149","https://openalex.org/W2197329920","https://openalex.org/W3023741826"],"related_works":["https://openalex.org/W6995679581","https://openalex.org/W7049226295","https://openalex.org/W616768548","https://openalex.org/W7034490215","https://openalex.org/W3140739583","https://openalex.org/W2751930545","https://openalex.org/W2984614598","https://openalex.org/W2586861715","https://openalex.org/W1981152584","https://openalex.org/W2951390066"],"abstract_inverted_index":{"By":[0],"using":[1,44],"particles,":[2,46],"beam":[3,77],"search":[4,78],"and":[5,23,70,79,89],"sequential":[6,80],"Monte":[7,81],"Carlo":[8,82],"can":[9,19],"approximate":[10],"distributions":[11],"in":[12],"an":[13,52],"extremely":[14],"flexible":[15,71],"manner.":[16],"However,":[17],"they":[18],"suffer":[20],"from":[21],"sparsity":[22],"inadequate":[24],"cover-age":[25],"on":[26,83],"large":[27],"state":[28,56],"spaces.":[29],"We":[30],"present":[31],"a":[32,64,68,85,90],"new":[33],"fil-tering":[34],"method":[35,75],"for":[36],"discrete":[37],"spaces":[38],"that":[39],"addresses":[40],"this":[41],"issue":[42],"by":[43],"\u201cabstract":[45],"\u201d":[47],"each":[48],"of":[49,55],"which":[50],"represents":[51],"entire":[53],"region":[54],"space.":[57],"These":[58],"abstract":[59],"particles":[60],"are":[61],"combined":[62],"into":[63],"hier-archical":[65],"decomposition,":[66],"yielding":[67],"compact":[69],"representation.":[72],"Empirically,":[73],"our":[74],"outperforms":[76],"both":[84],"text":[86],"reconstruction":[87],"task":[88],"multiple":[91],"object":[92],"tracking":[93],"task.":[94]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2016-06-24T00:00:00"}