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20222026
most citedPhysically recurrent neural networks for path-dependent heterogeneous materials: embedding constitutive models in a data-driven surrogate

81 citations · 86 across the 5 of their papers we have counts for

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cs.LG2026

On architectural choices for interpretability and thermodynamic consistency in Physically Recurrent Neural Networks in the low-data regime

M. A. Maia, K. A. Meyer, A. M. C. M. van Gils +2

In this paper, we unravel the effect of different decoder architectures on the interpretability of the latent space of the Physically Recurrent Neural Network. Particular emphasis…