{"id":"https://openalex.org/W4362603507","doi":"https://doi.org/10.1088/2632-2153/accace","title":"Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification","display_name":"Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification","publication_year":2023,"publication_date":"2023-04-05","ids":{"openalex":"https://openalex.org/W4362603507","doi":"https://doi.org/10.1088/2632-2153/accace"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/accace","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/accace","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/accace/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/accace/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011908450","display_name":"Cameron Gruich","orcid":"https://orcid.org/0000-0002-3801-1296"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cameron J Gruich","raw_affiliation_strings":["Department of Chemical Engineering, University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan, 48109-2800, UNITED STATES"],"raw_orcid":"https://orcid.org/0000-0002-3801-1296","affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan, 48109-2800, UNITED STATES","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057383845","display_name":"Varun Madhavan","orcid":"https://orcid.org/0000-0002-5107-4793"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Varun Madhavan","raw_affiliation_strings":["University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan, 48109-2800, UNITED STATES"],"raw_orcid":"https://orcid.org/0000-0002-5107-4793","affiliations":[{"raw_affiliation_string":"University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan, 48109-2800, UNITED STATES","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101934111","display_name":"Zhaoran Wang","orcid":"https://orcid.org/0000-0002-6617-4842"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yixin Wang","raw_affiliation_strings":["Department of Statistics, University of Michigan, 1085 South University Avenue, Ann Arbor, Michigan, 48109-1107, UNITED STATES"],"raw_orcid":"https://orcid.org/0000-0002-6617-4842","affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Michigan, 1085 South University Avenue, Ann Arbor, Michigan, 48109-1107, UNITED STATES","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026770434","display_name":"Bryan R. Goldsmith","orcid":"https://orcid.org/0000-0003-1264-8018"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan R Goldsmith","raw_affiliation_strings":["Department of Chemical Engineering, University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan, 48109-2800, UNITED STATES"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, University of Michigan, 2800 Plymouth Road, Ann Arbor, Michigan, 48109-2800, UNITED STATES","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011908450"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":1.3614,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.78417843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"4","issue":"2","first_page":"025019","last_page":"025019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":1.0,"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":1.0,"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/T10030","display_name":"Electrocatalysts for Energy Conversion","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10192","display_name":"Catalytic Processes in Materials Science","score":0.9878000020980835,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.5828295946121216},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5782467722892761},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.558797299861908},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.555411696434021},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5427497029304504},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4959014356136322},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46712642908096313},{"id":"https://openalex.org/keywords/heterogeneous-catalysis","display_name":"Heterogeneous catalysis","score":0.4333460330963135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3660026788711548},{"id":"https://openalex.org/keywords/catalysis","display_name":"Catalysis","score":0.3291251063346863},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3170854449272156},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.2937160134315491},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15598872303962708}],"concepts":[{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.5828295946121216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5782467722892761},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.558797299861908},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.555411696434021},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5427497029304504},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4959014356136322},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46712642908096313},{"id":"https://openalex.org/C175583648","wikidata":"https://www.wikidata.org/wiki/Q903156","display_name":"Heterogeneous catalysis","level":3,"score":0.4333460330963135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3660026788711548},{"id":"https://openalex.org/C161790260","wikidata":"https://www.wikidata.org/wiki/Q82264","display_name":"Catalysis","level":2,"score":0.3291251063346863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3170854449272156},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.2937160134315491},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15598872303962708},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2632-2153/accace","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/accace","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/accace/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:599808aa6dab40799d3dc21db3042f1a","is_oa":true,"landing_page_url":"https://doaj.org/article/599808aa6dab40799d3dc21db3042f1a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 4, Iss 2, p 025019 (2023)","raw_type":"article"},{"id":"pmh:oai:osti.gov:2422892","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2422892","pdf_url":null,"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":"doi:10.1088/2632-2153/accace","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/accace","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/accace/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.7300000190734863,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2974791382","display_name":null,"funder_award_id":"DGE 1841052","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320317220","display_name":"National Energy Research Scientific Computing Center","ror":"https://ror.org/05v3mvq14"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W204885769","https://openalex.org/W1534477342","https://openalex.org/W2006998081","https://openalex.org/W2010579662","https://openalex.org/W2022714449","https://openalex.org/W2025720061","https://openalex.org/W2046941888","https://openalex.org/W2130715829","https://openalex.org/W2162651021","https://openalex.org/W2266070239","https://openalex.org/W2517596840","https://openalex.org/W2548695521","https://openalex.org/W2766856748","https://openalex.org/W2768909439","https://openalex.org/W2778051509","https://openalex.org/W2799567665","https://openalex.org/W2810469995","https://openalex.org/W2890961624","https://openalex.org/W2907441256","https://openalex.org/W2917193084","https://openalex.org/W2945964866","https://openalex.org/W2947216528","https://openalex.org/W2959623824","https://openalex.org/W2965563166","https://openalex.org/W2995854597","https://openalex.org/W2997479617","https://openalex.org/W2997591727","https://openalex.org/W3000508506","https://openalex.org/W3012035124","https://openalex.org/W3013469885","https://openalex.org/W3014596384","https://openalex.org/W3025104221","https://openalex.org/W3043238520","https://openalex.org/W3089426421","https://openalex.org/W3092737886","https://openalex.org/W3093999435","https://openalex.org/W3102100346","https://openalex.org/W3103736477","https://openalex.org/W3104644561","https://openalex.org/W3109431282","https://openalex.org/W3111304214","https://openalex.org/W3134774296","https://openalex.org/W3164731060","https://openalex.org/W3185456481","https://openalex.org/W3195348523","https://openalex.org/W3197756890","https://openalex.org/W3201463170","https://openalex.org/W4210859464","https://openalex.org/W4213041519","https://openalex.org/W4213455561","https://openalex.org/W4214479070","https://openalex.org/W4225149098","https://openalex.org/W4226146754","https://openalex.org/W4283641078","https://openalex.org/W4283743489","https://openalex.org/W4283809948","https://openalex.org/W4286909196","https://openalex.org/W4287586570","https://openalex.org/W4287594739","https://openalex.org/W4292264370","https://openalex.org/W4294811426","https://openalex.org/W4297434546","https://openalex.org/W4298132949","https://openalex.org/W4310633502","https://openalex.org/W6617145748","https://openalex.org/W6674330103","https://openalex.org/W6683852811","https://openalex.org/W6730042731","https://openalex.org/W6739651123","https://openalex.org/W6746151544","https://openalex.org/W6753254651","https://openalex.org/W6767328938","https://openalex.org/W6768698167","https://openalex.org/W6779560548","https://openalex.org/W6784896029","https://openalex.org/W6801817941","https://openalex.org/W6802004894","https://openalex.org/W6810615853","https://openalex.org/W6839042332","https://openalex.org/W6840028651","https://openalex.org/W6841414473","https://openalex.org/W6843463674"],"related_works":["https://openalex.org/W2076536433","https://openalex.org/W90316445","https://openalex.org/W1991093342","https://openalex.org/W4293226380","https://openalex.org/W4327743613","https://openalex.org/W2965447900","https://openalex.org/W3199750033","https://openalex.org/W2374509987","https://openalex.org/W2078622645","https://openalex.org/W3163373470"],"abstract_inverted_index":{"Abstract":[0],"It":[1],"is":[2,104,116,143],"critical":[3],"that":[4],"machine":[5],"learning":[6],"(ML)":[7],"model":[8,141],"predictions":[9],"be":[10,119,146],"trustworthy":[11,128],"for":[12,123,131],"high-throughput":[13],"catalyst":[14,76],"discovery":[15],"approaches.":[16],"Uncertainty":[17],"quantification":[18],"(UQ)":[19],"methods":[20,32,49,82],"allow":[21],"estimation":[22],"of":[23,26,41,62,100,140,152],"the":[24,39,67,72,84],"trustworthiness":[25],"an":[27],"ML":[28],"model,":[29],"but":[30],"these":[31],"have":[33],"not":[34],"been":[35],"well":[36],"explored":[37],"in":[38,148],"field":[40],"heterogeneous":[42,75,132],"catalysis.":[43],"Herein,":[44],"we":[45],"investigate":[46],"different":[47],"UQ":[48,81,102,129],"applied":[50],"to":[51,58,83,118,145],"a":[52,120],"crystal":[53],"graph":[54],"convolutional":[55],"neural":[56,137],"network":[57],"predict":[59],"adsorption":[60,85],"energies":[61],"molecules":[63],"on":[64,107],"alloys":[65],"from":[66],"Open":[68],"Catalyst":[69],"2020":[70],"dataset,":[71],"largest":[73],"existing":[74],"dataset.":[77],"We":[78],"apply":[79],"three":[80],"energy":[86],"predictions,":[87],"namely":[88],"k":[89],"-fold":[90],"ensembling,":[91],"Monte":[92],"Carlo":[93],"dropout,":[94],"and":[95,112],"evidential":[96],"regression.":[97],"The":[98],"effectiveness":[99],"each":[101],"method":[103],"assessed":[105],"based":[106],"accuracy,":[108],"sharpness,":[109],"dispersion,":[110],"calibration,":[111],"tightness.":[113],"Evidential":[114],"regression":[115],"demonstrated":[117],"powerful":[121],"approach":[122],"rapidly":[124],"obtaining":[125],"tunable,":[126],"competitively":[127],"estimates":[130],"catalysis":[133],"applications":[134,151],"when":[135],"using":[136,154],"networks.":[138],"Recalibration":[139],"uncertainties":[142],"shown":[144],"essential":[147],"practical":[149],"screening":[150],"catalysts":[153],"uncertainties.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}