{"id":"https://openalex.org/W3091387572","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206667","title":"Amortized Mixture Prior for Variational Sequence Generation","display_name":"Amortized Mixture Prior for Variational Sequence Generation","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3091387572","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206667","mag":"3091387572"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5061908942","display_name":"Jen\u2010Tzung Chien","orcid":"https://orcid.org/0000-0003-3466-8941"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jen-Tzung Chien","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042510435","display_name":"Chih-Jung Tsai","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Jung Tsai","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":0.9481,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81372847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"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/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9980999827384949,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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":0.6740108728408813},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6576833724975586},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.636157751083374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6267535090446472},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.527868926525116},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4862021803855896},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4492562413215637},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41725456714630127},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4172455072402954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3889804184436798},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.0850382149219513}],"concepts":[{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.6740108728408813},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6576833724975586},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.636157751083374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6267535090446472},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.527868926525116},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4862021803855896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4492562413215637},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41725456714630127},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4172455072402954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3889804184436798},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0850382149219513},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W1583912456","https://openalex.org/W1909320841","https://openalex.org/W1933340426","https://openalex.org/W1959608418","https://openalex.org/W1999965501","https://openalex.org/W2036912417","https://openalex.org/W2049964102","https://openalex.org/W2056985955","https://openalex.org/W2064675550","https://openalex.org/W2099471712","https://openalex.org/W2110027950","https://openalex.org/W2113459411","https://openalex.org/W2129703168","https://openalex.org/W2173681125","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2242047860","https://openalex.org/W2267126114","https://openalex.org/W2327501763","https://openalex.org/W2405331948","https://openalex.org/W2409550820","https://openalex.org/W2423557781","https://openalex.org/W2549476280","https://openalex.org/W2560512785","https://openalex.org/W2572816092","https://openalex.org/W2586756136","https://openalex.org/W2587284713","https://openalex.org/W2592696501","https://openalex.org/W2606176153","https://openalex.org/W2606967921","https://openalex.org/W2624424670","https://openalex.org/W2753738274","https://openalex.org/W2796335507","https://openalex.org/W2804397569","https://openalex.org/W2937866564","https://openalex.org/W2953046278","https://openalex.org/W2953318193","https://openalex.org/W2962738009","https://openalex.org/W2962897886","https://openalex.org/W2962964508","https://openalex.org/W2963081964","https://openalex.org/W2963090522","https://openalex.org/W2963139417","https://openalex.org/W2963223306","https://openalex.org/W2963319343","https://openalex.org/W2963636093","https://openalex.org/W2963773425","https://openalex.org/W2963987720","https://openalex.org/W2964168257","https://openalex.org/W2964339599","https://openalex.org/W2964411643","https://openalex.org/W2972899181","https://openalex.org/W2988016942","https://openalex.org/W3007146018","https://openalex.org/W3037864170","https://openalex.org/W4289761690","https://openalex.org/W4293411878","https://openalex.org/W4294107275","https://openalex.org/W4297733427","https://openalex.org/W4297798428","https://openalex.org/W4297940714","https://openalex.org/W4320013936","https://openalex.org/W6610566761","https://openalex.org/W6635084905","https://openalex.org/W6639732818","https://openalex.org/W6640284076","https://openalex.org/W6640963894","https://openalex.org/W6676532846","https://openalex.org/W6676984168","https://openalex.org/W6685356407","https://openalex.org/W6714644935","https://openalex.org/W6729349781","https://openalex.org/W6730998768","https://openalex.org/W6731535438","https://openalex.org/W6733471323","https://openalex.org/W6736723571","https://openalex.org/W6738543193","https://openalex.org/W6738623590","https://openalex.org/W6738914561","https://openalex.org/W6743827229","https://openalex.org/W6747888389","https://openalex.org/W6749820799","https://openalex.org/W6751660789","https://openalex.org/W6752910514","https://openalex.org/W6753417141","https://openalex.org/W6779806341","https://openalex.org/W6780493881"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2988134182","https://openalex.org/W2770818364"],"abstract_inverted_index":{"Variational":[0],"autoencoder":[1,121],"(VAE)":[2],"is":[3,113],"a":[4,33],"popular":[5],"latent":[6,39,66,141],"variable":[7],"model":[8,28],"for":[9,65,123,149],"data":[10],"generation.":[11,125],"However,":[12],"in":[13,23,74,79,116],"natural":[14],"language":[15],"applications,":[16],"VAE":[17],"suffers":[18],"from":[19,41,86],"the":[20,27,61,71,87,135,139,145],"posterior":[21,29,136],"collapse":[22],"optimization":[24],"procedure":[25],"where":[26],"likely":[30],"collapses":[31],"to":[32,99],"standard":[34],"Gaussian":[35,62],"prior":[36,64,111],"which":[37],"disregards":[38],"semantics":[40],"sequence":[42,52,96,124],"data.":[43,53],"The":[44,81,93,108],"recurrent":[45,120],"decoder":[46],"accordingly":[47],"generates":[48],"du-plicate":[49],"or":[50],"noninformative":[51],"To":[54],"tackle":[55],"this":[56,58],"issue,":[57],"paper":[59],"adopts":[60],"mixture":[63,110],"variable,":[67],"and":[68,76,143,147],"simultaneously":[69],"fulfills":[70],"amortized":[72,88,109],"regularization":[73],"encoder":[75],"skip":[77,100],"connection":[78],"decoder.":[80],"noise":[82],"robust":[83],"prior,":[84],"learned":[85],"encoder,":[89],"becomes":[90,102],"semantically":[91],"meaningful.":[92],"prediction":[94],"of":[95,118],"samples,":[97],"due":[98],"connection,":[101],"contextually":[103],"precise":[104],"at":[105],"each":[106],"time.":[107],"(AMP)":[112],"then":[114],"formulated":[115],"construction":[117],"variational":[119],"(VRAE)":[122],"Experiments":[126],"on":[127],"different":[128],"tasks":[129],"show":[130],"that":[131],"AMP-VRAE":[132],"can":[133],"avoid":[134],"collapse,":[137],"learn":[138],"meaningful":[140],"features":[142],"improve":[144],"inference":[146],"generation":[148],"semantic":[150],"representation.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}