AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems

Wang, Yating; Leung, Wing Tat; Lin, Guang

doi:10.1137/21m1405289

AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems

Journal Article · 23 June 2022 · Multiscale Modeling & Simulation

DOI:https://doi.org/10.1137/21m1405289· OSTI ID:1980771

Wang, Yating ^[1]; Leung, Wing Tat ^[2]; Lin, Guang ^[3]

Department of Mathematics, Purdue University, West Lafayette, IN 47907 USA, and Department of Mathematics, University of Hong Kong, Hong Kong SAR, China ().
Department of Mathematics, University of California, Irvine, Irvine, CA 92697 USA ().
Department of Mathematics, School of Mechanical Engineering, Department of Statistics (Courtesy), and Department of Earth, Atmospheric, and Planetary Sciences (Courtesy), Purdue University, West Lafayette, IN 47907 USA ().

Not provided.

Research Organization:: Purdue Univ., West Lafayette, IN (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

DOE Contract Number:: SC0021142

OSTI ID:: 1980771

Journal Information:: Multiscale Modeling & Simulation, Vol. 20, Issue 2; ISSN 1540-3459

Publisher:: SIAM

Country of Publication:: United States

Language:: English

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