{"id":"https://openalex.org/W2072201410","doi":"https://doi.org/10.1109/ciss.2015.7086903","title":"Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture","display_name":"Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture","publication_year":2015,"publication_date":"2015-03-01","ids":{"openalex":"https://openalex.org/W2072201410","doi":"https://doi.org/10.1109/ciss.2015.7086903","mag":"2072201410"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2015.7086903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","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/A5073255290","display_name":"Daniel R. Mendat","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel R. Mendat","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103044811","display_name":"Sang Chin","orcid":"https://orcid.org/0000-0002-1913-4223"},"institutions":[{"id":"https://openalex.org/I2802946424","display_name":"Johns Hopkins University Applied Physics Laboratory","ror":"https://ror.org/029pp9z10","country_code":"US","type":"facility","lineage":["https://openalex.org/I145311948","https://openalex.org/I2802946424"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"None Sang Chin","raw_affiliation_strings":["Applied Physics Laboratory, Johns Hopkins University, Laurel, Maryland 20723, USA"],"affiliations":[{"raw_affiliation_string":"Applied Physics Laboratory, Johns Hopkins University, Laurel, Maryland 20723, USA","institution_ids":["https://openalex.org/I2802946424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083177159","display_name":"Steve Furber","orcid":"https://orcid.org/0000-0002-6524-3367"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Steve Furber","raw_affiliation_strings":["School of Computer Science, The University of Manchester, M13 9PL, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Manchester, M13 9PL, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057789499","display_name":"Andreas G. Andreou","orcid":"https://orcid.org/0000-0003-3826-600X"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas G. Andreou","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.678,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":13,"citation_normalized_percentile":{"value":0.732489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":88},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9971,"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/T10320","display_name":"Neural Networks and Applications","score":0.9971,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.997,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9852,"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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.88130444},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.55474067}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.88130444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7126597},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.69217664},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.56041783},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.55474067},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.54273593},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.51466924},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4697129},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.35182807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3367499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18871966},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1705907},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0971508},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.057834536},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2015.7086903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.67,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":20,"referenced_works":["https://openalex.org/W1511986666","https://openalex.org/W1600293573","https://openalex.org/W1663973292","https://openalex.org/W1989012887","https://openalex.org/W1990262300","https://openalex.org/W1997267143","https://openalex.org/W2017540033","https://openalex.org/W2025516544","https://openalex.org/W2034333464","https://openalex.org/W2051137788","https://openalex.org/W2135194391","https://openalex.org/W2153041354","https://openalex.org/W2159951683","https://openalex.org/W2163179684","https://openalex.org/W2163738067","https://openalex.org/W2395355800","https://openalex.org/W2979006918","https://openalex.org/W3203992401","https://openalex.org/W4212863985","https://openalex.org/W4231517135"],"related_works":["https://openalex.org/W4387459935","https://openalex.org/W4382561696","https://openalex.org/W4285308918","https://openalex.org/W3031505884","https://openalex.org/W3015991694","https://openalex.org/W2986579802","https://openalex.org/W2971712727","https://openalex.org/W2951049725","https://openalex.org/W2908450434","https://openalex.org/W2895519962"],"abstract_inverted_index":{"We":[0,54],"present":[1,55],"a":[2,18,51],"combined":[3],"hardware/software":[4],"architecture":[5,27],"to":[6,50,64],"perform":[7],"Markov":[8],"Chain":[9],"Monte":[10],"Carlo":[11],"sampling":[12,59,88],"on":[13,78],"probabilistic":[14],"graphical":[15],"models":[16],"in":[17,39],"brain-inspired,":[19],"energy-aware":[20],"manner.":[21],"By":[22],"combining":[23],"massively-parallel":[24],"neuromorphic":[25],"hardware":[26],"(SpiNNaker)":[28],"with":[29],"algorithms":[30],"we've":[31],"have":[32],"developed":[33],"for":[34],"the":[35,65,70,73,85,97],"event-based":[36],"framework":[37],"employed":[38],"SpiNNaker,":[40],"we":[41],"achieve":[42],"large":[43],"speedups":[44],"when":[45],"performing":[46],"inference":[47],"as":[48],"compared":[49],"traditional":[52],"PC.":[53],"results":[56],"from":[57],"two":[58,74],"approaches":[60,75],"both":[61],"well":[62],"suited":[63],"SpiNNaker":[66],"architecture.":[67],"Neural":[68],"sampling,":[69],"first":[71],"of":[72,81,96],"relies":[76],"directly":[77],"simulating":[79],"networks":[80],"spiking":[82],"neurons":[83],"while":[84],"second,":[86],"Gibb's":[87],"is":[89],"more":[90],"flexible":[91],"but":[92],"still":[93],"takes":[94],"advantage":[95],"hardware's":[98],"event-handling":[99],"capabilities.":[100]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2072201410","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":3}],"updated_date":"2025-01-05T14:56:23.152672","created_date":"2016-06-24"}