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Title: Data-driven identification of 2D Partial Differential Equations using extracted physical features

Journal Article · · Computer Methods in Applied Mechanics and Engineering

Not Available

Sponsoring Organization:
USDOE
OSTI ID:
1836170
Journal Information:
Computer Methods in Applied Mechanics and Engineering, Journal Name: Computer Methods in Applied Mechanics and Engineering Journal Issue: C Vol. 381; ISSN 0045-7825
Publisher:
ElsevierCopyright Statement
Country of Publication:
Netherlands
Language:
English

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DGM: A deep learning algorithm for solving partial differential equations journal December 2018
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Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks
  • Vlachas, Pantelis R.; Byeon, Wonmin; Wan, Zhong Y.
  • Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 474, Issue 2213 https://doi.org/10.1098/rspa.2017.0844
journal May 2018
Data-driven discovery of partial differential equations journal April 2017
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Data-Driven Identification of Parametric Partial Differential Equations journal January 2019
The Mythos of Model Interpretability: In machine learning, the concept of interpretability is both important and slippery. journal June 2018
Energy decay for damped wave equations on partially rectangular domains journal January 2007

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