{"id":"https://openalex.org/W3093932597","doi":"https://doi.org/10.1109/icassp39728.2021.9413712","title":"Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering","display_name":"Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3093932597","doi":"https://doi.org/10.1109/icassp39728.2021.9413712","mag":"3093932597"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.13694","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011960578","display_name":"Aaqib Saeed","orcid":"https://orcid.org/0000-0003-1473-0322"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Aaqib Saeed","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065912572","display_name":"David Grangier","orcid":"https://orcid.org/0000-0002-8847-9532"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Grangier","raw_affiliation_strings":["Google Research, Paris, France","Google Research,Paris,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Google Research,Paris,France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065100569","display_name":"Olivier Pietquin","orcid":"https://orcid.org/0000-0002-5386-465X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Olivier Pietquin","raw_affiliation_strings":["Google Research, Paris, France","Google Research,Paris,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Google Research,Paris,France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047639590","display_name":"Neil Zeghidour","orcid":"https://orcid.org/0000-0001-6896-3987"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neil Zeghidour","raw_affiliation_strings":["Google Research, Paris, France","Google Research,Paris,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Google Research,Paris,France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6235,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55817462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1255","last_page":"1259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10581","display_name":"Neural dynamics and brain function","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7409546971321106},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6540773510932922},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6157405972480774},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5662621259689331},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.5640780925750732},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4960218369960785},{"id":"https://openalex.org/keywords/shuffling","display_name":"Shuffling","score":0.48580479621887207},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4853912591934204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4521581530570984},{"id":"https://openalex.org/keywords/charm","display_name":"Charm (quantum number)","score":0.41177529096603394},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4071904420852661},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3723478317260742},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33157339692115784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10413655638694763},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06672748923301697},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.064056396484375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7409546971321106},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6540773510932922},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6157405972480774},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5662621259689331},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.5640780925750732},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4960218369960785},{"id":"https://openalex.org/C167927819","wikidata":"https://www.wikidata.org/wiki/Q1930567","display_name":"Shuffling","level":2,"score":0.48580479621887207},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4853912591934204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4521581530570984},{"id":"https://openalex.org/C2781339351","wikidata":"https://www.wikidata.org/wiki/Q2639620","display_name":"Charm (quantum number)","level":2,"score":0.41177529096603394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4071904420852661},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3723478317260742},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33157339692115784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10413655638694763},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06672748923301697},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.064056396484375},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2010.13694","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.13694","pdf_url":"https://arxiv.org/pdf/2010.13694","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/2e243eaf-d9cc-4907-b68d-9cac8137fb96","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/2e243eaf-d9cc-4907-b68d-9cac8137fb96","pdf_url":"https://pure.tue.nl/ws/files/369930861/Learning_From_Heterogeneous_Eeg_Signals_with_Differentiable_Channel_Reordering.pdf","source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Saeed, A, Grangier, D, Pietquin, O & Zeghidour, N 2021, Learning from heterogeneous EEG signals with differentiable channel reordering. in ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)., 9413712, Institute of Electrical and Electronics Engineers, pp. 1255-1259, 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021, Virtual, Toronto, Canada, 6/06/21. https://doi.org/10.1109/ICASSP39728.2021.9413712","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:3093932597","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2010.13694","pdf_url":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2010.13694","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.13694","pdf_url":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.17023/zvq6-7075","is_oa":true,"landing_page_url":"https://doi.org/10.17023/zvq6-7075","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","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":"Audiovisual"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2010.13694","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.13694","pdf_url":"https://arxiv.org/pdf/2010.13694","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309327","display_name":"Google","ror":"https://ror.org/00njsd438"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3093932597.pdf"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W114225708","https://openalex.org/W1522301498","https://openalex.org/W1556131344","https://openalex.org/W1677182931","https://openalex.org/W2008205547","https://openalex.org/W2050265252","https://openalex.org/W2081931753","https://openalex.org/W2125388816","https://openalex.org/W2138190513","https://openalex.org/W2140413964","https://openalex.org/W2314733761","https://openalex.org/W2345279893","https://openalex.org/W2502312327","https://openalex.org/W2526755872","https://openalex.org/W2557301950","https://openalex.org/W2559463885","https://openalex.org/W2604096629","https://openalex.org/W2741907166","https://openalex.org/W2889245000","https://openalex.org/W2902034646","https://openalex.org/W2904559787","https://openalex.org/W2915893085","https://openalex.org/W2963403868","https://openalex.org/W2963861107","https://openalex.org/W2995516697","https://openalex.org/W3003074332","https://openalex.org/W3102455230","https://openalex.org/W3192807527","https://openalex.org/W6604702074","https://openalex.org/W6631190155","https://openalex.org/W6633205339","https://openalex.org/W6680455596","https://openalex.org/W6723019446","https://openalex.org/W6724804524","https://openalex.org/W6739901393","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W3160453855","https://openalex.org/W3179461162","https://openalex.org/W3196236986","https://openalex.org/W2986273262","https://openalex.org/W3172787012","https://openalex.org/W3133247227","https://openalex.org/W3045676091","https://openalex.org/W2921618710","https://openalex.org/W3174832115","https://openalex.org/W2964263619","https://openalex.org/W2977961849","https://openalex.org/W3015738170","https://openalex.org/W3135201683","https://openalex.org/W2583984586","https://openalex.org/W2939217021","https://openalex.org/W3170048064","https://openalex.org/W2792332872","https://openalex.org/W2949532563","https://openalex.org/W2935707851","https://openalex.org/W3211510458"],"abstract_inverted_index":{"We":[0,90],"propose":[1],"CHARM,":[2],"a":[3,7,54,67,81],"method":[4,114],"for":[5],"training":[6],"single":[8],"neural":[9],"network":[10],"across":[11,44],"inconsistent":[12],"input":[13,60,64,110],"channels.":[14,111],"Our":[15,46],"work":[16],"is":[17,71],"motivated":[18],"by":[19],"Electroencephalography":[20],"(EEG),":[21],"where":[22],"data":[23],"collection":[24],"protocols":[25],"from":[26,58],"different":[27,125],"headsets":[28],"result":[29],"in":[30],"varying":[31],"channel":[32,83],"ordering":[33,84],"and":[34,62,73,98,107],"number,":[35],"which":[36],"limits":[37],"the":[38,100,116],"feasibility":[39],"of":[40,102,109,118],"transferring":[41],"trained":[42],"systems":[43],"datasets.":[45],"approach":[47],"builds":[48],"upon":[49],"attention":[50],"mechanisms":[51],"to":[52,66,85],"estimate":[53],"latent":[55],"reordering":[56],"matrix":[57],"each":[59],"signal":[61],"map":[63],"channels":[65],"canonical":[68],"order.":[69],"CHARM":[70,103],"differentiable":[72],"can":[74],"be":[75],"composed":[76],"further":[77],"with":[78,124],"architectures":[79],"expecting":[80],"consistent":[82],"build":[86],"end-to-end":[87],"trainable":[88],"classifiers.":[89],"perform":[91],"experiments":[92],"on":[93],"four":[94],"EEG":[95],"classification":[96],"datasets":[97,122],"demonstrate":[99],"efficacy":[101],"via":[104],"simulated":[105],"shuffling":[106],"masking":[108],"Moreover,":[112],"our":[113],"improves":[115],"transfer":[117],"pre-trained":[119],"representations":[120],"between":[121],"collected":[123],"protocols.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
