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			<depositor_name>Institute for Advanced Materials Research Press</depositor_name>
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				<full_title>Journal of Computational and Data-Driven Materials Engineering</full_title>
				<abbrev_title>J. Comput. Data-Driven Mater. Eng.</abbrev_title>
				<issn>3149-9368</issn>
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					<year>2022</year>
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					<volume>1</volume>
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				<issue>2</issue>
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					<title>Uncertainty Quantification for ML Interatomic Potentials: A Review of Methods, Hidden Assumptions, and Unresolved Questions</title>
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          					<person_name sequence="first" contributor_role="author">
            <given_name>Daniel</given_name>
            <surname>Fischer</surname>
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            <given_name>Laura</given_name>
            <surname>Meier</surname>
					</person_name>
          					<person_name sequence="additional" contributor_role="author">
            <given_name>Thomas</given_name>
            <surname>Braun</surname>
					</person_name>
          					<person_name sequence="additional" contributor_role="author">
            <given_name>Stefan</given_name>
            <surname>Koch</surname>
					</person_name>
          					<person_name sequence="additional" contributor_role="author">
            <given_name>Felix</given_name>
            <surname>Roth</surname>
					</person_name>
          				</contributors>
								<publication_date>
					<year>2022</year>
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