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Unravelling Neural Networks with Structure-Preserving Computing
Unravelling Neural Networks with Structure-Preserving Computing
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Machine learning for closure models (MSc thesis)
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Towards interpretable machine-learning models by extracting interpretable latent variables
Mimetic and hierarchical neural networks
Dynamic neural networks and their relation to state-space methods
Energy-conserving neural network closure models for fluid flow problems
Machine learning for analysis and control of complex fluid flows
Neural networks for N-body simulations
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