{"id":"https://openalex.org/W2986113209","doi":"https://doi.org/10.23919/eusipco.2019.8902811","title":"Training Variational Autoencoders with Discrete Latent Variables Using Importance Sampling","display_name":"Training Variational Autoencoders with Discrete Latent Variables Using Importance Sampling","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2986113209","doi":"https://doi.org/10.23919/eusipco.2019.8902811","mag":"2986113209"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8902811","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"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/A5021977554","display_name":"Alexander Bartler","orcid":null},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alexander Bartler","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049738037","display_name":"Felix Wiewel","orcid":null},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix Wiewel","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048602838","display_name":"Lukas Mauch","orcid":"https://orcid.org/0000-0001-9212-899X"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lukas Mauch","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101717968","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-8322-117X"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021977554"],"corresponding_institution_ids":["https://openalex.org/I100066346"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.12760962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9934999942779541,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9930999875068665,"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/latent-variable","display_name":"Latent variable","score":0.7675942182540894},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.699321985244751},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6193053722381592},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.590060830116272},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5746607780456543},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5493572950363159},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5364186763763428},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4881161153316498},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.48131024837493896},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4443443715572357},{"id":"https://openalex.org/keywords/bernoullis-principle","display_name":"Bernoulli's principle","score":0.4382096827030182},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.41177576780319214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3573852777481079},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33963191509246826},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.29510533809661865},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2441406548023224},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20153024792671204},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17485401034355164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.0849674642086029}],"concepts":[{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.7675942182540894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.699321985244751},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6193053722381592},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.590060830116272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5746607780456543},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5493572950363159},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5364186763763428},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4881161153316498},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.48131024837493896},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4443443715572357},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.4382096827030182},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.41177576780319214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3573852777481079},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33963191509246826},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.29510533809661865},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2441406548023224},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20153024792671204},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17485401034355164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0849674642086029},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2019.8902811","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","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":30,"referenced_works":["https://openalex.org/W1956333070","https://openalex.org/W1959608418","https://openalex.org/W2119717200","https://openalex.org/W2242818861","https://openalex.org/W2431962807","https://openalex.org/W2522389179","https://openalex.org/W2547875792","https://openalex.org/W2548228487","https://openalex.org/W2551604710","https://openalex.org/W2556467266","https://openalex.org/W2750384547","https://openalex.org/W2752796333","https://openalex.org/W2785362611","https://openalex.org/W2963226019","https://openalex.org/W2963799213","https://openalex.org/W2963851840","https://openalex.org/W3098957257","https://openalex.org/W3153872861","https://openalex.org/W4293415974","https://openalex.org/W4297663084","https://openalex.org/W6640963894","https://openalex.org/W6690026940","https://openalex.org/W6718140377","https://openalex.org/W6718362372","https://openalex.org/W6727296518","https://openalex.org/W6729832310","https://openalex.org/W6730091202","https://openalex.org/W6730333270","https://openalex.org/W6743688258","https://openalex.org/W6745515306"],"related_works":["https://openalex.org/W2988134182","https://openalex.org/W2470043383","https://openalex.org/W2953501176","https://openalex.org/W2965095304","https://openalex.org/W3034474024","https://openalex.org/W2770818364","https://openalex.org/W4317242571","https://openalex.org/W2944085132","https://openalex.org/W2616125534","https://openalex.org/W2770703741"],"abstract_inverted_index":{"The":[0],"Variational":[1],"Autoencoder":[2],"(VAE)":[3],"is":[4,12,57,73,104],"a":[5,38,97],"popular":[6],"generative":[7],"latent":[8,22,68,92,126],"variable":[9],"model":[10],"that":[11],"often":[13],"used":[14],"for":[15,100],"representation":[16],"learning.":[17],"Standard":[18],"VAEs":[19,65,86,119],"assume":[20],"continuous-valued":[21],"variables":[23],"and":[24,47,115,123],"are":[25],"trained":[26],"by":[27],"maximization":[28],"of":[29,41],"the":[30,42,101,113],"evidence":[31],"lower":[32],"bound":[33],"(ELBO).":[34],"Conventional":[35],"methods":[36],"obtain":[37],"differentiable":[39,98],"estimate":[40],"ELBO":[43,102],"with":[44,50,66,87,121],"reparametrized":[45,71],"sampling":[46,72],"optimize":[48],"it":[49],"Stochastic":[51],"Gradient":[52],"Descend":[53],"(SGD).":[54],"However,":[55],"this":[56,77],"not":[58,74],"possible":[59],"if":[60],"we":[61,79,95,111],"want":[62],"to":[63,84],"train":[64,85,116],"discrete-valued":[67],"variables,":[69],"since":[70],"possible.":[75],"In":[76,109],"paper,":[78],"propose":[80],"an":[81],"easy":[82],"method":[83],"binary":[88],"or":[89],"categorically":[90,124],"valued":[91],"representations.":[93],"Therefore,":[94],"use":[96],"estimator":[99],"which":[103],"based":[105],"on":[106,128],"importance":[107],"sampling.":[108],"experiments,":[110],"verify":[112],"approach":[114],"two":[117,129],"different":[118,130],"architectures":[120],"Bernoulli":[122],"distributed":[125],"representations":[127],"benchmark":[131],"datasets.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}