{"id":"https://openalex.org/W3201765225","doi":"https://doi.org/10.3929/ethz-b-000490637","title":"Navigating the Latent Spaces of Deep Neural Networks using Adversarial Techniques","display_name":"Navigating the Latent Spaces of Deep Neural Networks using Adversarial Techniques","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3201765225","doi":"https://doi.org/10.3929/ethz-b-000490637","mag":"3201765225"},"language":"en","primary_location":{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/490637","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/490637","pdf_url":"http://hdl.handle.net/20.500.11850/490637","source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/doctoralThesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/20.500.11850/490637","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072556870","display_name":"Yannic Kilcher","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kilcher, Yannic","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5072556870"],"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":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9965000152587891,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9965000152587891,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.96670001745224,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9653000235557556,"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/adversarial-system","display_name":"Adversarial system","score":0.7969480752944946},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5775693655014038},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.529591977596283},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5246784090995789},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48982784152030945},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46104520559310913},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39822864532470703},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3850921392440796}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7969480752944946},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5775693655014038},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.529591977596283},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5246784090995789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48982784152030945},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46104520559310913},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39822864532470703},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3850921392440796}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/490637","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/490637","pdf_url":"http://hdl.handle.net/20.500.11850/490637","source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/doctoralThesis"},{"id":"doi:10.3929/ethz-b-000490637","is_oa":true,"landing_page_url":"https://doi.org/10.3929/ethz-b-000490637","pdf_url":null,"source":{"id":"https://openalex.org/S7407051236","display_name":"ETH Z\u00fcrich Research Collection","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Other"},{"id":"mag:3201765225","is_oa":false,"landing_page_url":"https://www.research-collection.ethz.ch/handle/20.500.11850/490637","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/490637","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/490637","pdf_url":"http://hdl.handle.net/20.500.11850/490637","source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/doctoralThesis"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3201765225.pdf","grobid_xml":"https://content.openalex.org/works/W3201765225.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3100490876","https://openalex.org/W3178524591","https://openalex.org/W3211209003","https://openalex.org/W3214319091","https://openalex.org/W3015573934","https://openalex.org/W3035554136","https://openalex.org/W3212912391","https://openalex.org/W3157232645","https://openalex.org/W2765655769","https://openalex.org/W2801372087","https://openalex.org/W3170848816","https://openalex.org/W2581263672","https://openalex.org/W2948082843","https://openalex.org/W3130140376","https://openalex.org/W3026524884","https://openalex.org/W3127062532","https://openalex.org/W3042239647","https://openalex.org/W3082870144","https://openalex.org/W2980690519","https://openalex.org/W2896487848"],"abstract_inverted_index":{"Deep":[0,28],"learning":[1,223],"has":[2],"become":[3],"a":[4,94,148,156,166,188],"pervasive":[5],"tool":[6],"in":[7,16,88,147,162,183,198,204],"the":[8,33,45,80,106,193,210],"field":[9],"of":[10,35,50,54,64,82,96,195,212],"machine":[11],"learning,":[12,39],"delivering":[13],"unprecedented":[14],"advances":[15],"fields":[17],"such":[18],"as":[19],"computer":[20],"vision,":[21],"natural":[22],"language":[23],"processing,":[24],"and":[25,85,130,172,186,207,218],"speech":[26],"recognition.":[27],"neural":[29,124,145,163],"networks,":[30],"which":[31,117,135],"comprise":[32,136],"class":[34],"models":[36,139],"behind":[37],"deep":[38,89,222],"transform":[40],"their":[41],"input":[42,101],"signal":[43],"into":[44,57],"desired":[46,107],"output":[47,127],"by":[48,142],"means":[49],"sequential,":[51],"layer-wise":[52],"transformation":[53],"that":[55,98,122],"data":[56,102,120],"successive":[58],"latent":[59,66,83],"representations.":[60],"The":[61,109],"careful":[62],"study":[63],"these":[65],"representations":[67],"can":[68],"open":[69],"up":[70],"novel":[71],"ways":[72,206],"to":[73,104,126],"build":[74],"better":[75,216],"models.":[76],"This":[77],"work":[78,201],"investigates":[79],"connection":[81,168],"spaces":[84],"adversarial":[86,115,132,160,170],"techniques":[87,92],"learning.":[90],"Adversarial":[91],"are":[93,114,118,154],"set":[95],"methods":[97],"deliberately":[99],"craft":[100],"perturbations":[103,121],"achieve":[105],"goal.":[108],"two":[110,144],"most":[111],"notable":[112],"examples":[113,161],"examples,":[116],"imperceptible":[119],"force":[123],"classifiers":[125],"high-confidence":[128],"errors,":[129],"generative":[131,138],"networks":[133,146],"(GANs),":[134],"state-of-the-art":[137],"for":[140,159,180,191,209],"images":[141],"arranging":[143],"minimax":[149],"game.":[150],"Specifically,":[151],"our":[152],"contributions":[153],"(1)":[155],"statistical":[157],"detector":[158],"classifiers,":[164],"(2)":[165],"formal":[167],"between":[169],"training":[171],"spectral":[173],"norm":[174],"regularization,":[175],"(3)":[176],"an":[177],"improved":[178],"method":[179],"semantic":[181],"interpolation":[182],"implicit":[184],"models,":[185],"(4)":[187],"quantifiable":[189],"metric":[190],"measuring":[192],"suitability":[194],"prior":[196],"distributions":[197],"GANs.":[199],"Our":[200],"is":[202],"extendable":[203],"many":[205],"allows":[208],"development":[211],"higher-performing,":[213],"more":[214,219],"robust,":[215],"understandable,":[217],"easily":[220],"trainable":[221],"systems.":[224]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}