Uncertainty quantification of graph convolution neural network models of evolving processes
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Publication:6588354
DOI10.1016/j.cma.2024.117195MaRDI QIDQ6588354
Ravi G. Patel, Jeremiah Hauth, Xun Huan, Reese Edward Jones, Cosmin Safta
Publication date: 15 August 2024
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
neural networksuncertainty quantificationrecurrent networksneural ordinary differential equationsStein variational gradient descent
Applications of statistics to physics (62P35) Crystals in solids (74N05) Stochastic and other probabilistic methods applied to problems in solid mechanics (74S60)
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