L. Morand

发表

Machine learning-based sampling of virtual experiments within the full stress state to identify parameters of anisotropic yield models

W. Volk, A. Butz, D. Helm, 2022, 2211.00090.

Efficient Exploration of Microstructure-Property Spaces via Active Learning

D. Helm, N. Link, L. Morand, 2022, Frontiers in Materials.

Neural Networks for Constitutive Modeling -- From Universal Function Approximators to Advanced Models and the Integration of Physics

D. Helm, L. Morand, Johannes Dornheim, 2023, 2302.14397.

A knowledge-based surrogate modeling approach for cup drawing with limited data

L. Morand, D. Helm, R. Iza-Teran, 2019, IOP Conference Series: Materials Science and Engineering.

Compensating data shortages in manufacturing with monotonicity knowledge pdf

Martin von Kurnatowski, Jochen Schmid, Patrick Link, 2020, Algorithms.

A multi-task learning-based optimization approach for finding diverse sets of material microstructures with desired properties and its application to texture optimization

D. Helm, N. Link, L. Morand, 2021, ArXiv.

Deep reinforcement learning methods for structure-guided processing path optimization pdf

Lukas Morand, Dirk Helm, Samuel Zeitvogel, 2020, J. Intell. Manuf..

Structure-Guided Processing Path Optimization with Deep Reinforcement Learning

D. Helm, N. Link, Samuel Zeitvogel, 2020, ArXiv.

A mixture of experts approach to handle ambiguities in parameter identification problems in material modeling

Lukas Morand, Dirk Helm, D. Helm, 2019, Computational Materials Science.

Neural Networks for Constitutive Modeling: From Universal Function Approximators to Advanced Models and the Integration of Physics

D. Helm, L. Morand, Johannes Dornheim, 2023, Archives of Computational Methods in Engineering.

A new machine learning based method for sampling virtual experiments and its effect on the parameter identification for anisotropic yield models

W. Volk, A. Butz, D. Helm, 2021 .

A multi-task learning-based optimization approach for finding diverse sets of microstructures with desired properties

D. Helm, N. Link, L. Morand, 2023, Journal of Intelligent Manufacturing.

Deep reinforcement learning methods for structure-guided processing path optimization

Norbert Link, Lukas Morand, Dirk Helm, 2020, Journal of Intelligent Manufacturing.