HIGHLIGHTS
- who: Martin Eigel et al. from the Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany have published the Article: Topology Optimisation under Uncertainties with Neural Networks, in the Journal: Algorithms 2022, 15, 241. of /2022/
- what: To alleviate this computational burden the authors develop two neural network architectures (NN) that are capable of predicting the gradient step of the optimisation procedure. The authors extend the previous work by introducing Deep Neuronal Networks (DNN) that are designed to provide a prediction of the next gradient step. The aim of this paper is to devise new . . .
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