{"id":"https://openalex.org/W4361193212","doi":"https://doi.org/10.48550/arxiv.2303.14554","title":"Deep Kernel Methods Learn Better: From Cards to Process Optimization","display_name":"Deep Kernel Methods Learn Better: From Cards to Process Optimization","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4361193212","doi":"https://doi.org/10.48550/arxiv.2303.14554"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2303.14554","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2303.14554","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113087821","display_name":"Mani Valleti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Valleti, Mani","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034418849","display_name":"Rama k. Vasudevan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vasudevan, Rama k.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013879711","display_name":"Maxim Ziatdinov","orcid":"https://orcid.org/0000-0003-2570-4592"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziatdinov, Maxim A.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048552375","display_name":"Sergei V. Kalinin","orcid":"https://orcid.org/0000-0001-5354-6152"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalinin, Sergei V.","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.824426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":67,"max":78},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9788,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9788,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9676,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9629,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9167098},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5997104},{"id":"https://openalex.org/keywords/representation","display_name":"Representation","score":0.5442091},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature Learning","score":0.52562827},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.46516657}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9167098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6550404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6228546},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6127666},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5997104},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5442091},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.52562827},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.50555706},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.50518996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48916152},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48911697},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.48016873},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4750709},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4684204},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.46516657},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.243449},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2064631},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08766472},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2303.14554","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.14554","pdf_url":"http://arxiv.org/pdf/2303.14554","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2303.14554","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2303.14554","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4389832810","https://openalex.org/W4313561566","https://openalex.org/W4281663961","https://openalex.org/W4220682630","https://openalex.org/W3208888551","https://openalex.org/W3208386644","https://openalex.org/W3181622257","https://openalex.org/W3163146846","https://openalex.org/W2983142544","https://openalex.org/W2891059443"],"abstract_inverted_index":{"The":[0,190],"ability":[1],"of":[2,40,61,70,86,146],"deep":[3,51],"learning":[4,53,89,105,161],"methods":[5],"to":[6,17,119,122,143],"perform":[7],"classification":[8],"and":[9,24,38,50,96,111,140,187],"regression":[10],"tasks":[11],"relies":[12],"heavily":[13],"on":[14],"their":[15],"capacity":[16],"uncover":[18],"manifolds":[19,42,157],"in":[20,76,149,171,178],"high-dimensional":[21],"data":[22,73,94,138],"spaces":[23],"project":[25],"them":[26],"into":[27],"low-dimensional":[28],"representation":[29],"spaces.":[30],"In":[31,55],"this":[32,132],"study,":[33],"we":[34],"investigate":[35],"the":[36,41,56,59,62,68,71,77,79,93,128,144,195,199],"structure":[37,60,166],"character":[39],"generated":[43],"by":[44,67],"classical":[45],"variational":[46],"autoencoder":[47],"(VAE)":[48],"approaches":[49],"kernel":[52],"(DKL).":[54],"former":[57],"case,":[58],"latent":[63,80,113,156],"space":[64,114],"is":[65,116],"determined":[66],"properties":[69],"input":[72],"alone,":[74],"while":[75],"latter,":[78],"manifold":[81],"forms":[82],"as":[83,127,182],"a":[84,108,135,163],"result":[85],"an":[87],"active":[88,104,160],"process":[90],"that":[91,101,155,175,193],"balances":[92],"distribution":[95],"target":[97],"functionalities.":[98],"We":[99,130],"show":[100],"DKL":[102],"with":[103],"can":[106],"produce":[107],"more":[109,117,164],"compact":[110],"smooth":[112],"which":[115],"conducive":[118],"optimization":[120,145,168],"compared":[121],"previously":[123],"reported":[124],"methods,":[125],"such":[126,181],"VAE.":[129],"demonstrate":[131],"behavior":[133],"using":[134],"simple":[136],"cards":[137],"set":[139],"extend":[141],"it":[142],"domain-generated":[147],"trajectories":[148],"physical":[150],"systems.":[151],"Our":[152],"findings":[153],"suggest":[154],"constructed":[158],"through":[159],"have":[162],"beneficial":[165],"for":[167],"problems,":[169],"especially":[170],"feature-rich":[172],"target-poor":[173],"scenarios":[174],"are":[176],"common":[177],"domain":[179],"sciences,":[180],"materials":[183],"synthesis,":[184],"energy":[185],"storage,":[186],"molecular":[188],"discovery.":[189],"jupyter":[191],"notebooks":[192],"encapsulate":[194],"complete":[196],"analysis":[197],"accompany":[198],"article.":[200]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4361193212","counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-01-04T17:18:39.274328","created_date":"2023-03-31"}