Machine learning for structure-guided materials and process design von Morand, Lukas, Iraki, Tarek, Dornheim, Johannes, Sandfeld, Stefan, Link, Norbert, Helm, Dirk

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Efficient Exploration of Microstructure-Property Spaces via Active Learning von Morand, Lukas, Link, Norbert, Iraki, Tarek, Dornheim, Johannes, Helm, Dirk

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Combined crystal plasticity and phase-field method for recrystallization in a process chain of sheet metal production von Vondrous, Alexander, Bienger, Pierre, Schreijäg, Simone, Selzer, Michael, Schneider, Daniel, Nestler, Britta, Helm, Dirk, Mönig, Reiner

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A mixture of experts approach to handle ambiguities in parameter identification problems in material modeling von Morand, Lukas, Helm, Dirk

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A convex fourth order yield function for orthotropic metal plasticity von Uppaluri, Rohith, Helm, Dirk

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A thermodynamically consistent model for elastoplasticity, recovery, recrystallization and grain coarsening von Kertsch, Lukas, Helm, Dirk

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Thermomechanical characterization of 22MnB5 steels with special emphasis on stress relaxation and creep behavior von Uppaluri, Rohith, Helm, Dirk

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Machine learning-based sampling of virtual experiments within the full stress state von Wessel, Alexander, Morand, Lukas, Butz, Alexander, Helm, Dirk, Volk, Wolfram

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Optimizing machine learning yield functions using query-by-committee for support vector classification with a dynamic stopping criterion von Shoghi, Ronak, Morand, Lukas, Helm, Dirk, Hartmaier, Alexander

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Stress computation in finite thermoviscoplasticity von Helm, Dirk

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A multi-task learning-based optimization approach for finding diverse sets of microstructures with desired properties von Iraki, Tarek, Morand, Lukas, Dornheim, Johannes, Link, Norbert, Helm, Dirk

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Site-specific quasi in situ investigation of primary static recrystallization in a low carbon steel von Diehl, Martin, Kertsch, Lukas, Traka, Konstantina, Helm, Dirk, Raabe, Dierk

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Accurate distances measures and machine learning of the texture-property relation for crystallographic textures represented by one-point statistics von Iraki, Tarek, Morand, Lukas, Link, Norbert, Sandfeld, Stefan, Helm, Dirk

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Modelling grain growth in the framework of Rational Extended Thermodynamics von Kertsch, Lukas, Helm, Dirk

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Neural Networks for Constitutive Modeling: From Universal Function Approximators to Advanced Models and the Integration of Physics von Dornheim, Johannes, Morand, Lukas, Nallani, Hemanth Janarthanam, Helm, Dirk

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Twinning and detwinning during compression–tension loading measured by quasi in situ electron backscatter diffraction tracing in Mg–3Al–Zn rolled sheet von Zheng, Li, Zhang, Shi-Hong, Helm, Dirk, Song, Hong-Wu, Song, Guang-Sheng, Ye, Neng-Yong

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Site-specific quasi in situ investigation of primary static recrystallization in a low carbon steel von Diehl, Martin, Kertsch, Lukas, Traka, Konstantina, Helm, Dirk, Raabe, Dierk

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Deep reinforcement learning methods for structure-guided processing path optimization von Dornheim, Johannes, Morand, Lukas, Zeitvogel, Samuel, Iraki, Tarek, Link, Norbert, Helm, Dirk

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Thermomechanical representation of the stored energy during plastic deformation von Helm, Dirk

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Thermodynamically consistent modelling of recrystallization and grain coarsening in precipitation‐hardened alloys von Kertsch, Lukas, Helm, Dirk

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