{"id":"https://openalex.org/W4404037271","doi":"https://doi.org/10.1109/mlsp58920.2024.10734787","title":"Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design","display_name":"Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design","publication_year":2024,"publication_date":"2024-09-22","ids":{"openalex":"https://openalex.org/W4404037271","doi":"https://doi.org/10.1109/mlsp58920.2024.10734787"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp58920.2024.10734787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp58920.2024.10734787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.osti.gov/servlets/purl/2550614","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002054189","display_name":"A N M Nafiz Abeer","orcid":"https://orcid.org/0009-0004-8134-1604"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"A N M Nafiz Abeer","raw_affiliation_strings":["Texas A&#x0026;M University,Department of Electrical and Computer Engineering,College Station,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&#x0026;M University,Department of Electrical and Computer Engineering,College Station,TX,USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064019866","display_name":"Sanket Jantre","orcid":"https://orcid.org/0000-0003-3611-0255"},"institutions":[{"id":"https://openalex.org/I200870766","display_name":"Brookhaven National Laboratory","ror":"https://ror.org/02ex6cf31","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I200870766","https://openalex.org/I39565521","https://openalex.org/I4210142672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanket Jantre","raw_affiliation_strings":["Computational Science Initiative, Brookhaven National Laboratory,Upton,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computational Science Initiative, Brookhaven National Laboratory,Upton,NY,USA","institution_ids":["https://openalex.org/I200870766"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032837897","display_name":"Nathan M. Urban","orcid":"https://orcid.org/0000-0002-2264-3512"},"institutions":[{"id":"https://openalex.org/I200870766","display_name":"Brookhaven National Laboratory","ror":"https://ror.org/02ex6cf31","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I200870766","https://openalex.org/I39565521","https://openalex.org/I4210142672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan M Urban","raw_affiliation_strings":["Computational Science Initiative, Brookhaven National Laboratory,Upton,NY,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computational Science Initiative, Brookhaven National Laboratory,Upton,NY,USA","institution_ids":["https://openalex.org/I200870766"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081620315","display_name":"Byung-Jun Yoon","orcid":"https://orcid.org/0000-0001-9328-1101"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Byung-Jun Yoon","raw_affiliation_strings":["Texas A&#x0026;M University,Department of Electrical and Computer Engineering,College Station,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&#x0026;M University,Department of Electrical and Computer Engineering,College Station,TX,USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002054189"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.2226,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48713078,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9984999895095825,"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":0.9984999895095825,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9682000279426575,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.7030611038208008},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.6825623512268066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6313872337341309},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6151352524757385},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6007770299911499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5092426538467407},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36207860708236694},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16590666770935059}],"concepts":[{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.7030611038208008},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.6825623512268066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6313872337341309},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6151352524757385},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6007770299911499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5092426538467407},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36207860708236694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16590666770935059},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mlsp58920.2024.10734787","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp58920.2024.10734787","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:osti.gov:2550614","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2550614","pdf_url":"https://www.osti.gov/servlets/purl/2550614","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"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":null}],"best_oa_location":{"id":"pmh:oai:osti.gov:2550614","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2550614","pdf_url":"https://www.osti.gov/servlets/purl/2550614","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"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":null},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5633341255","display_name":null,"funder_award_id":"No. DE-SC0012704","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G6357584807","display_name":null,"funder_award_id":"SC0012704","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G7642226822","display_name":null,"funder_award_id":"DE-SC0012704","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404037271.pdf","grobid_xml":"https://content.openalex.org/works/W4404037271.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W1522301498","https://openalex.org/W2064963922","https://openalex.org/W2140838683","https://openalex.org/W2167141095","https://openalex.org/W2225156818","https://openalex.org/W2529996553","https://openalex.org/W2610148085","https://openalex.org/W2619890685","https://openalex.org/W2785023044","https://openalex.org/W2786722833","https://openalex.org/W2951266961","https://openalex.org/W2962764565","https://openalex.org/W2963028280","https://openalex.org/W2966294393","https://openalex.org/W3009610697","https://openalex.org/W3014339631","https://openalex.org/W3035236454","https://openalex.org/W3040246664","https://openalex.org/W3044724994","https://openalex.org/W3104956673","https://openalex.org/W3159054876","https://openalex.org/W3176507666","https://openalex.org/W3181995918","https://openalex.org/W3193572680","https://openalex.org/W4221155493","https://openalex.org/W4283697502","https://openalex.org/W4319074048","https://openalex.org/W4392904041","https://openalex.org/W4400008163","https://openalex.org/W6617145748","https://openalex.org/W6631190155","https://openalex.org/W6666624420","https://openalex.org/W6680607141","https://openalex.org/W6739000085","https://openalex.org/W6747927160","https://openalex.org/W6751979845","https://openalex.org/W6764214684","https://openalex.org/W6765542386","https://openalex.org/W6779439776","https://openalex.org/W6780409856","https://openalex.org/W6794739717","https://openalex.org/W6797862432","https://openalex.org/W6798300011","https://openalex.org/W6839212538"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"Deep":[0],"generative":[1,25,67],"models":[2,28],"have":[3,29],"been":[4],"accelerating":[5],"the":[6,58,76,84,87,93,97,103,124,138,155],"inverse":[7],"design":[8,23,27],"process":[9],"in":[10,20,42,86,107],"material":[11],"and":[12,70,146],"drug":[13],"design.":[14],"Unlike":[15],"their":[16,47],"counterpart":[17],"property":[18],"predictors":[19],"typical":[21],"molecular":[22,26,68,151],"frameworks,":[24],"seen":[30],"fewer":[31],"efforts":[32],"on":[33,57,150],"uncertainty":[34,85,106],"quantification":[35],"(UQ)":[36],"d":[37],"ue":[38],"to":[39,82,101,131],"computational":[40],"challenges":[41],"Bayesian":[43],"inference":[44],"posed":[45],"by":[46,74,153],"large":[48],"number":[49],"of":[50,123],"parameters.":[51,89],"In":[52],"this":[53,72],"work,":[54],"we":[55,91],"focus":[56],"junction-tree":[59],"variational":[60],"autoencoder":[61],"(JT-VAE),":[62],"a":[63],"popular":[64],"model":[65,88,105,125,156],"for":[66],"design,":[69],"address":[71],"issue":[73],"leveraging":[75],"low":[77],"dimensional":[78,111],"active":[79,98],"subspace":[80,99],"(AS)":[81],"capture":[83],"Specifically,":[90],"approximate":[92],"posterior":[94],"distribution":[95],"over":[96],"parameters":[100],"estimate":[102],"epistemic":[104,159],"an":[108],"extremely":[109],"high":[110],"parameter":[112],"space.":[113],"The":[114],"proposed":[115],"UQ":[116,145],"scheme":[117],"does":[118],"not":[119],"require":[120],"any":[121,132],"alteration":[122],"architecture,":[126],"making":[127],"it":[128],"readily":[129],"applicable":[130],"pre-trained":[133],"model.":[134],"Our":[135],"experiments":[136],"demonstrate":[137],"efficacy":[139],"o":[140],"f":[141],"t":[142],"he":[143],"AS-based":[144],"its":[147],"potential":[148],"impact":[149],"optimization":[152],"exploring":[154],"diversity":[157],"under":[158],"uncertainty.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}
