Physics-Informed Neural networks for Advanced modeling
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Updated
Jul 1, 2024 - Python
Physics-Informed Neural networks for Advanced modeling
Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid flow dynamics
TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks (UQPINNs).
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