{"id":"https://openalex.org/W4388427707","doi":"https://doi.org/10.1109/iv60283.2023.00055","title":"Information Plane Analysis Visualization in Deep Learning via Transfer Entropy","display_name":"Information Plane Analysis Visualization in Deep Learning via Transfer Entropy","publication_year":2023,"publication_date":"2023-07-25","ids":{"openalex":"https://openalex.org/W4388427707","doi":"https://doi.org/10.1109/iv60283.2023.00055"},"language":"en","primary_location":{"id":"doi:10.1109/iv60283.2023.00055","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv60283.2023.00055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 27th International Conference Information Visualisation (IV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2404.01364","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054926104","display_name":"Adrian Moldovan","orcid":"https://orcid.org/0000-0003-1393-2723"},"institutions":[{"id":"https://openalex.org/I3123573182","display_name":"Transylvania University of Bra\u0219ov","ror":"https://ror.org/01cg9ws23","country_code":"RO","type":"education","lineage":["https://openalex.org/I3123573182"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Adrian Moldovan","raw_affiliation_strings":["Transilvania University,Department of Electronics and Computers,Braşov,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Transilvania University,Department of Electronics and Computers,Braşov,Romania","institution_ids":["https://openalex.org/I3123573182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040393337","display_name":"Angel Ca\u0163aron","orcid":"https://orcid.org/0000-0002-3986-5437"},"institutions":[{"id":"https://openalex.org/I3123573182","display_name":"Transylvania University of Bra\u0219ov","ror":"https://ror.org/01cg9ws23","country_code":"RO","type":"education","lineage":["https://openalex.org/I3123573182"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Angel Ca\u0163aron","raw_affiliation_strings":["Transilvania University,Department of Electronics and Computers,Braşov,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Transilvania University,Department of Electronics and Computers,Braşov,Romania","institution_ids":["https://openalex.org/I3123573182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018888157","display_name":"R\u0103zvan Andonie","orcid":"https://orcid.org/0000-0002-6015-3151"},"institutions":[{"id":"https://openalex.org/I3123573182","display_name":"Transylvania University of Bra\u0219ov","ror":"https://ror.org/01cg9ws23","country_code":"RO","type":"education","lineage":["https://openalex.org/I3123573182"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"R\u0103zvan Andonie","raw_affiliation_strings":["Transilvania University,Department of Electronics and Computers,Braşov,Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Transilvania University,Department of Electronics and Computers,Braşov,Romania","institution_ids":["https://openalex.org/I3123573182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3123573182"],"apc_list":null,"apc_paid":null,"fwci":0.7979,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.69593822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"22","issue":null,"first_page":"278","last_page":"285"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9905999898910522,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9900000095367432,"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/information-bottleneck-method","display_name":"Information bottleneck method","score":0.940085768699646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7217891812324524},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.6150596141815186},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6026504635810852},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5812445878982544},{"id":"https://openalex.org/keywords/transfer-entropy","display_name":"Transfer entropy","score":0.5698080062866211},{"id":"https://openalex.org/keywords/information-transfer","display_name":"Information transfer","score":0.551461935043335},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.533739447593689},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5209397077560425},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.49345579743385315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4879295527935028},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4619844853878021},{"id":"https://openalex.org/keywords/information-visualization","display_name":"Information visualization","score":0.4109114110469818},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34521716833114624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.187414288520813},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.1338176131248474}],"concepts":[{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.940085768699646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7217891812324524},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.6150596141815186},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6026504635810852},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5812445878982544},{"id":"https://openalex.org/C182049051","wikidata":"https://www.wikidata.org/wiki/Q17147155","display_name":"Transfer entropy","level":3,"score":0.5698080062866211},{"id":"https://openalex.org/C8854915","wikidata":"https://www.wikidata.org/wiki/Q4350200","display_name":"Information transfer","level":2,"score":0.551461935043335},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.533739447593689},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5209397077560425},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.49345579743385315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4879295527935028},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4619844853878021},{"id":"https://openalex.org/C185578843","wikidata":"https://www.wikidata.org/wiki/Q10609775","display_name":"Information visualization","level":3,"score":0.4109114110469818},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34521716833114624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.187414288520813},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.1338176131248474},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iv60283.2023.00055","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv60283.2023.00055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 27th International Conference Information Visualisation (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2404.01364","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.01364","pdf_url":"https://arxiv.org/pdf/2404.01364","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2404.01364","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.01364","pdf_url":"https://arxiv.org/pdf/2404.01364","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388427707.pdf","grobid_xml":"https://content.openalex.org/works/W4388427707.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1535837316","https://openalex.org/W1686946872","https://openalex.org/W2014389247","https://openalex.org/W2041782669","https://openalex.org/W2050334647","https://openalex.org/W2055632453","https://openalex.org/W2056501338","https://openalex.org/W2079656335","https://openalex.org/W2082674974","https://openalex.org/W2100659887","https://openalex.org/W2118858186","https://openalex.org/W2142858796","https://openalex.org/W2151252184","https://openalex.org/W2163605009","https://openalex.org/W2315805880","https://openalex.org/W2335728318","https://openalex.org/W2593634001","https://openalex.org/W2625728394","https://openalex.org/W2750384547","https://openalex.org/W2779018802","https://openalex.org/W2803439868","https://openalex.org/W2880214242","https://openalex.org/W2898404165","https://openalex.org/W2942056403","https://openalex.org/W2943160321","https://openalex.org/W2951841718","https://openalex.org/W2962807446","https://openalex.org/W2964184826","https://openalex.org/W2982402336","https://openalex.org/W2994763368","https://openalex.org/W2996320484","https://openalex.org/W2998745691","https://openalex.org/W3022414928","https://openalex.org/W3120740533","https://openalex.org/W3173703884","https://openalex.org/W3199738405","https://openalex.org/W4210414750","https://openalex.org/W4283691501","https://openalex.org/W4285109787","https://openalex.org/W4285276944","https://openalex.org/W4293469690","https://openalex.org/W4297749952","https://openalex.org/W4309793939","https://openalex.org/W6637108112","https://openalex.org/W6677919164","https://openalex.org/W6684191040","https://openalex.org/W6703116779","https://openalex.org/W6739141896","https://openalex.org/W6751983209","https://openalex.org/W6754984521","https://openalex.org/W6756362675"],"related_works":["https://openalex.org/W2070945723","https://openalex.org/W2050334647","https://openalex.org/W1999409691","https://openalex.org/W3598568","https://openalex.org/W1595266364","https://openalex.org/W3032013634","https://openalex.org/W2492100837","https://openalex.org/W4224256769","https://openalex.org/W4310557244","https://openalex.org/W348369544"],"abstract_inverted_index":{"In":[0,122],"a":[1,35,61,101],"feedforward":[2],"network,":[3],"Transfer":[4],"Entropy":[5],"(TE)":[6],"can":[7,128],"be":[8],"used":[9,64],"to":[10,30,65,124,145],"measure":[11],"the":[12,22,31,42,55,67,75,78,84,89,93,163],"influence":[13],"that":[14,98],"one":[15],"layer":[16],"has":[17],"on":[18],"another":[19],"by":[20,82,110],"quantifying":[21],"information":[23,53,72,87,147],"transfer":[24,148],"between":[25,69,104,132,149],"them":[26],"during":[27],"training.":[28],"According":[29],"Information":[32,57,79,154],"Bottleneck":[33,80],"principle,":[34],"neural":[36,150],"model's":[37],"internal":[38],"representation":[39],"should":[40],"compress":[41],"input":[43,90],"data":[44,91],"as":[45,47],"much":[46],"possible":[48],"while":[49],"still":[50],"retaining":[51],"sufficient":[52],"about":[54],"output.":[56],"Plane":[58,155],"analysis":[59],"is":[60,100,113],"visualization":[62],"technique":[63],"understand":[66],"trade-off":[68],"compression":[70,106],"and":[71,107,152],"preservation":[73],"in":[74,88,138],"context":[76],"of":[77,86],"method":[81],"plotting":[83],"amount":[85],"against":[92],"compressed":[94],"representation.":[95],"The":[96],"claim":[97],"there":[99],"causal":[102],"link":[103],"information-theoretic":[105],"generalization,":[108],"measured":[109],"mutual":[111,125],"information,":[112,126],"plausible,":[114],"but":[115],"results":[116],"from":[117],"different":[118],"studies":[119],"are":[120],"conflicting.":[121],"contrast":[123],"TE":[127,144],"capture":[129],"temporal":[130],"relationships":[131],"variables.":[133],"To":[134],"explore":[135],"such":[136],"links,":[137],"our":[139],"novel":[140],"approach":[141],"we":[142],"use":[143],"quantify":[146],"layers":[151],"perform":[153],"analysis.":[156],"We":[157],"obtained":[158],"encouraging":[159],"experimental":[160],"results,":[161],"opening":[162],"possibility":[164],"for":[165],"further":[166],"investigations.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2023-11-07T00:00:00"}