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Evidential regression is demonstrated to be a powerful approach for rapidly obtaining tunable, competitively trustworthy UQ estimates for heterogeneous catalysis applications when using neural networks. Recalibration of model uncertainties is shown to be essential in practical screening applications of catalysts using uncertainties.<\/jats:p>","DOI":"10.1088\/2632-2153\/accace","type":"journal-article","created":{"date-parts":[[2023,4,5]],"date-time":"2023-04-05T22:43:01Z","timestamp":1680734581000},"page":"025019","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification"],"prefix":"10.1088","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3801-1296","authenticated-orcid":true,"given":"Cameron J","family":"Gruich","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5107-4793","authenticated-orcid":true,"given":"Varun","family":"Madhavan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6617-4842","authenticated-orcid":true,"given":"Yixin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bryan R","family":"Goldsmith","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2023,5,3]]},"reference":[{"key":"mlstaccacebib1","doi-asserted-by":"publisher","first-page":"2311","DOI":"10.1002\/aic.16198","article-title":"Machine learning for heterogeneous catalyst design and discovery","volume":"64","author":"Goldsmith","year":"2018","journal-title":"AIChE J."},{"key":"mlstaccacebib2","doi-asserted-by":"publisher","DOI":"10.1088\/2515-7639\/ab084b","article-title":"From DFT to machine learning: recent approaches to materials science\u2014a review","volume":"2","author":"Schleder","year":"2019","journal-title":"J. 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