Work

Variational Deep Material Network: Enabling efficient aleatoric UQ in structure-property modeling

Year: 2025

Type: report

Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)

DOI: 10.2172/3453411

Authors: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), Andreas Robertson, USDOE National Nuclear Security Administration (NNSA), Brad Boyce, Samuel Inman, Ashley Lenau, Ricardo Lebensohn, Dongil Shin

Institutions: Sandia National Laboratories, Los Alamos National Laboratory, Pohang University of Science and Technology

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W7204008906

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