Deep Learning in Computational Mechanics - An Introductory Course - Stefan Kollmannsberger; Davide D'Angella; Moritz Jokeit; Leon Herrmann (Springer, 2021)

GPU-Accelerated Simulation Ensembles of Stochastic Reaction Networks. - Till Köster; Leon Herrmann; Philipp Andelfinger; Adelinde M. Uhrmacher (WSC, 2022)

Transfer Learning Enhanced Full Waveform Inversion. - Stefan Kollmannsberger; Divya Singh 001; Leon Herrmann (AIM, 2023)

On the Use of Neural Networks for Full Waveform Inversion. - Leon Herrmann; Tim Bürchner; Felix Dietrich; Stefan Kollmannsberger (CoRR, 2023)

From ductile damage to unilateral contact via point-wise implicit discontinuity at the infinitesimal element level. - Alireza Daneshyar; Leon Herrmann; Stefan Kollmannsberger (CoRR, 2023)

Deep Learning in Deterministic Computational Mechanics. - Leon Herrmann; Stefan Kollmannsberger (CoRR, 2023)

The Discontinuous Strain Method: accurately representing fatigue and failure. - Leon Herrmann; Alireza Daneshyar; Stefan Kollmannsberger (CoRR, 2023)

Neural Networks for Generating Better Local Optima in Topology Optimization. - Leon Herrmann; Ole Sigmund; Viola Muning Li; Christian Vogl; Stefan Kollmannsberger (CoRR, 2024)

Accelerating Full Waveform Inversion By Transfer Learning. - Divya Shyam Singh 001; Leon Herrmann; Qing Sun; Tim Bürchner; Felix Dietrich; Stefan Kollmannsberger (CoRR, 2024)

Generative adversarial networks enable outlier detection and property monitoring for additive manufacturing of complex structures. - Alexander Henkes; Leon Herrmann; Henning Wessels; Stefan Kollmannsberger (Eng. Appl. Artif. Intell., 2024)