{"id":"https://openalex.org/W4400231146","doi":"https://doi.org/10.1109/iscas58744.2024.10558060","title":"A Memristor Circuit Implementing Tunable Stochastic Distributions for Bayesian Inference and Monte Carlo Sampling","display_name":"A Memristor Circuit Implementing Tunable Stochastic Distributions for Bayesian Inference and Monte Carlo Sampling","publication_year":2024,"publication_date":"2024-05-19","ids":{"openalex":"https://openalex.org/W4400231146","doi":"https://doi.org/10.1109/iscas58744.2024.10558060"},"language":"en","primary_location":{"id":"doi:10.1109/iscas58744.2024.10558060","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iscas58744.2024.10558060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5080254002","display_name":"Adil Malik","orcid":"https://orcid.org/0000-0001-5257-2455"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adil Malik","raw_affiliation_strings":["Imperial College London,Electrical and Electronic Engineering,London,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London,Electrical and Electronic Engineering,London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048618563","display_name":"Christos Papavassiliou","orcid":"https://orcid.org/0000-0002-8003-2146"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christos Papavassiliou","raw_affiliation_strings":["Imperial College London,Electrical and Electronic Engineering,London,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London,Electrical and Electronic Engineering,London,United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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/T10320","display_name":"Neural Networks and Applications","score":0.9886999726295471,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9882000088691711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6961883306503296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6230575442314148},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5717903971672058},{"id":"https://openalex.org/keywords/memristor","display_name":"Memristor","score":0.5669190287590027},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5590873956680298},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5470519661903381},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5116038918495178},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.49230992794036865},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4811452627182007},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.41689541935920715},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.39394980669021606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.281232088804245},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.20723241567611694},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18443703651428223},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1755075454711914},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11467063426971436},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0946485698223114},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.05952131748199463}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6961883306503296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230575442314148},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5717903971672058},{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.5669190287590027},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5590873956680298},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5470519661903381},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5116038918495178},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.49230992794036865},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4811452627182007},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.41689541935920715},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.39394980669021606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.281232088804245},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.20723241567611694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18443703651428223},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1755075454711914},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11467063426971436},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0946485698223114},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.05952131748199463},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas58744.2024.10558060","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iscas58744.2024.10558060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Circuits and Systems (ISCAS)","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":8,"referenced_works":["https://openalex.org/W2245173025","https://openalex.org/W2600578627","https://openalex.org/W3165790670","https://openalex.org/W4288389052","https://openalex.org/W4306406679","https://openalex.org/W4384517567","https://openalex.org/W4390693343","https://openalex.org/W6789718423"],"related_works":["https://openalex.org/W2305965628","https://openalex.org/W4226314133","https://openalex.org/W3186706744","https://openalex.org/W227870709","https://openalex.org/W3087071515","https://openalex.org/W2959831473","https://openalex.org/W4323055853","https://openalex.org/W2291370119","https://openalex.org/W4288282435","https://openalex.org/W3000025630"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,79],"present":[4],"a":[5,73,84],"novel":[6],"memristive":[7],"circuit":[8,19,66,76],"that":[9],"is":[10],"capable":[11],"of":[12,25,59,75],"generating":[13],"tunable":[14,94],"stochastic":[15],"distributions.":[16],"The":[17],"proposed":[18],"leverages":[20],"the":[21,26,39,48,55,60,65,69,81],"inherent":[22],"read":[23],"noise":[24,57],"memristor":[27],"and":[28,43,54,67,86,101],"utilises":[29],"feedback":[30],"to":[31],"shape":[32],"its":[33],"spectrum":[34],"into":[35],"achieving":[36],"control":[37],"over":[38],"output":[40,56,70],"distributions":[41,71,95],"mean":[42],"standard":[44],"deviation.":[45],"We":[46,62],"analyse":[47],"relationship":[49],"between":[50],"various":[51],"loop":[52],"parameters":[53],"characteristics":[58],"circuit.":[61],"experimentally":[63],"build":[64],"investigate":[68],"for":[72,98],"range":[74],"parameters.":[77],"Lastly,":[78],"develop":[80],"theory,":[82],"propose":[83],"system":[85],"demonstrate":[87],"an":[88],"example,":[89],"where":[90],"such":[91],"circuits":[92],"generate":[93],"in":[96],"hardware":[97],"Bayesian":[99],"Inference":[100],"Monte-Carlo":[102],"sampling.":[103]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}