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math.NA2026
Compression of Polyconvex Envelopes of Isotropic Functions via Monotonic Input Convex Neural Networks
Timo Neumeier, Julian Salmon
This work presents a novel neural-network compression approach for polyconvex envelopes of isotropic functions. The approach relies on a classical sufficient criterion for polyconv…
math.NA2025
Neural Network Enhanced Polyconvexification of Isotropic Energy Densities in Computational Mechanics
Loïc Balazi, Timo Neumeier, Malte A. Peter +1
We present a neural network approach for fast evaluation of parameter-dependent polyconvex envelopes, which are crucial in computational mechanics. Our method uses a neural network…
math.NA2023
Computational polyconvexification of isotropic functions
Timo Neumeier, Malte A. Peter, Daniel Peterseim +1
Based on the characterization of the polyconvex envelope of isotropic functions by their signed singular value representations, we propose a simple algorithm for the numerical appr…