{"id":"https://openalex.org/W6990577063","doi":null,"title":"Distributions in Semantic Space","display_name":"Distributions in Semantic Space","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W6990577063"},"language":"en","primary_location":{"id":"pmh:oai:uwspace.uwaterloo.ca:10012/20506","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10012/20506","pdf_url":"https://uwspace.uwaterloo.ca/bitstreams/126488c4-09e1-4bbc-8b04-e32011b42a7e/download","source":{"id":"https://openalex.org/S4306401661","display_name":"UWSpace (University of Waterloo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I151746483","host_organization_name":"University of Waterloo","host_organization_lineage":["https://openalex.org/I151746483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Doctoral Thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://uwspace.uwaterloo.ca/bitstreams/126488c4-09e1-4bbc-8b04-e32011b42a7e/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018267778","display_name":"Kira A. Selby","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Selby, Kira","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5018267778"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9848999977111816,"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":0.9848999977111816,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.008700000122189522,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0010999999940395355,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/word-embeddings","display_name":"word embeddings","score":0.6330000162124634},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"distributional semantics","score":0.6320000290870667},{"id":"https://openalex.org/keywords/latent-space","display_name":"latent space","score":0.597000002861023},{"id":"https://openalex.org/keywords/probabilistic-robustness","display_name":"probabilistic robustness","score":0.7900000214576721},{"id":"https://openalex.org/keywords/natural-language-models","display_name":"natural language models","score":0.6340000033378601},{"id":"https://openalex.org/keywords/universal-approximation","display_name":"universal approximation","score":0.7329999804496765},{"id":"https://openalex.org/keywords/kullback-leibler-divergence","display_name":"Kullback-Leibler divergence","score":0.7789999842643738},{"id":"https://openalex.org/keywords/mutual-information","display_name":"mutual information","score":0.9900000095367432},{"id":"https://openalex.org/keywords/few-shot-image-generation","display_name":"few-shot image generation","score":0.9800000190734863},{"id":"https://openalex.org/keywords/zero-shot-image-generation","display_name":"zero-shot image generation","score":0.7139999866485596},{"id":"https://openalex.org/keywords/context-distribution","display_name":"context distribution","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7023000121116638},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6230999827384949},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5105999708175659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4675000011920929},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3750999867916107},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35269999504089355},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.3199999928474426},{"id":"https://openalex.org/C153024298","wikidata":"https://www.wikidata.org/wiki/Q3030678","display_name":"Hellinger distance","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:uwspace.uwaterloo.ca:10012/20506","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10012/20506","pdf_url":"https://uwspace.uwaterloo.ca/bitstreams/126488c4-09e1-4bbc-8b04-e32011b42a7e/download","source":{"id":"https://openalex.org/S4306401661","display_name":"UWSpace (University of Waterloo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I151746483","host_organization_name":"University of Waterloo","host_organization_lineage":["https://openalex.org/I151746483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Doctoral Thesis"}],"best_oa_location":{"id":"pmh:oai:uwspace.uwaterloo.ca:10012/20506","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10012/20506","pdf_url":"https://uwspace.uwaterloo.ca/bitstreams/126488c4-09e1-4bbc-8b04-e32011b42a7e/download","source":{"id":"https://openalex.org/S4306401661","display_name":"UWSpace (University of Waterloo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I151746483","host_organization_name":"University of Waterloo","host_organization_lineage":["https://openalex.org/I151746483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Doctoral Thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6990577063.pdf","grobid_xml":"https://content.openalex.org/works/W6990577063.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1816313093","https://openalex.org/W1972099155","https://openalex.org/W2083875149","https://openalex.org/W2092939357","https://openalex.org/W2127265454","https://openalex.org/W2133413932","https://openalex.org/W2150879893","https://openalex.org/W2157331557","https://openalex.org/W2194321275","https://openalex.org/W2478536981","https://openalex.org/W2493916176","https://openalex.org/W2561995736","https://openalex.org/W2741602058","https://openalex.org/W2765961751","https://openalex.org/W2767899794","https://openalex.org/W2799054028","https://openalex.org/W2888158354","https://openalex.org/W2895957115","https://openalex.org/W2896457183","https://openalex.org/W2965373594","https://openalex.org/W2981540061","https://openalex.org/W2984060780","https://openalex.org/W2990062453","https://openalex.org/W3030163527","https://openalex.org/W3034296706","https://openalex.org/W3092987574","https://openalex.org/W3168114125","https://openalex.org/W3168867926","https://openalex.org/W3174480022","https://openalex.org/W4232613155","https://openalex.org/W4288817207"],"related_works":["https://openalex.org/W2474771165","https://openalex.org/W7098663861","https://openalex.org/W2970789589","https://openalex.org/W4295528389","https://openalex.org/W2342823808","https://openalex.org/W3112765659","https://openalex.org/W6884931726","https://openalex.org/W2460814443","https://openalex.org/W3156761522","https://openalex.org/W2175749012"],"abstract_inverted_index":{"This":[0],"thesis":[1],"is":[2,205],"an":[3],"investigation":[4],"of":[5,11,15,32,44,69,78,133,147,153,180,225,271],"the":[6,30,119,144,269,272],"powerful":[7],"and":[8,49,126,139,217,238,274],"flexible":[9],"applications":[10],"analyzing":[12],"empirical":[13],"distributions":[14,97,109],"vectors":[16],"within":[17],"latent":[18],"spaces.":[19],"These":[20],"methods":[21],"have":[22],"historically":[23],"been":[24],"applied":[25],"with":[26,71],"great":[27],"success":[28],"to":[29,36,52,64,85,100,129,184,207,246,252,282,291],"domain":[31],"word":[33,148],"embeddings,":[34],"leading":[35],"improvements":[37],"in":[38,87,98,167],"robustness":[39,86,166],"against":[40],"polysemy,":[41],"unsupervised":[42,57],"inference":[43],"hierarchical":[45,103],"relationships":[46,104],"between":[47,96,105,197],"words,":[48],"even":[50],"used":[51],"shatter":[53],"existing":[54,67,185,220,261],"benchmarks":[55],"on":[56,74,176,222],"translation.":[58],"\\n":[59,81,90,112,158,187,241],"\\nThis":[60],"work":[61,155],"will":[62,122],"serve":[63],"extend":[65],"these":[66,115],"lines":[68],"inquiry,":[70],"a":[72,130,161,177,190,209,223,248,286],"focus":[73],"two":[75],"key":[76,151],"areas":[77],"further":[79],"research:":[80],"a)":[82],"Probabilistic":[83],"approaches":[84],"natural":[88,168],"language.":[89],"b)":[91],"Approximating":[92],"general":[93,102,191],"distance":[94,195,232],"functions":[95,196,216,233],"order":[99],"infer":[101],"words":[106],"from":[107],"their":[108],"over":[110],"contexts.":[111],"\\nMotivated":[113],"by":[114],"initial":[116],"research":[117],"directions,":[118],"resulting":[120],"investigations":[121],"then":[123],"demonstrate":[124],"novel":[125],"significant":[127],"contributions":[128,152],"diverse":[131],"range":[132,179],"problems":[134],"across":[135],"many":[136],"different":[137],"fields":[138],"domains":[140],"-":[141],"far":[142],"beyond":[143],"narrow":[145],"scope":[146],"embeddings.":[149],"The":[150,171,202,256],"this":[154,244],"are":[156],"threefold:":[157],"1.":[159],"Proposing":[160],"probabilistic,":[162],"model-agnostic":[163],"framework":[164],"for":[165,193,212,289],"language":[169],"models.":[170],"proposed":[172,203,257],"model":[173],"improves":[174],"performance":[175],"wide":[178],"downstream":[181],"tasks":[182],"compared":[183],"baselines.":[186],"2.":[188],"Constructing":[189],"architecture":[192,204,245],"modelling":[194],"multiple":[198],"permutation":[199],"invariant":[200],"sets.":[201],"proved":[206],"be":[208],"universal":[210],"approximator":[211],"all":[213,219,260],"partially":[214],"permutation-invariant":[215],"outperforms":[218,259],"baselines":[221,263],"number":[224],"set-based":[226,250],"tasks,":[227],"as":[228,230,235],"well":[229],"approximating":[231],"such":[234],"KL":[236],"Divergence":[237],"Mutual":[239],"Information.":[240],"3.":[242],"Leveraging":[243],"define":[247],"novel,":[249],"approach":[251,258],"few-shot":[253],"image":[254],"generation.":[255,294],"image-to-image":[262],"without":[264],"making":[265,284],"restrictive":[266],"assumptions":[267],"about":[268],"structure":[270],"training":[273],"evaluation":[275],"sets":[276],"that":[277],"might":[278],"limit":[279],"its":[280],"ability":[281],"generalize,":[283],"it":[285],"promising":[287],"candidate":[288],"scaling":[290],"true":[292],"zero-shot":[293]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}