Analyzing dynamical disorder for charge transport in organic semiconductors via machine learning. - Patrick Reiser; Manuel Konrad; Artem Fediai; Salvador León; Wolfgang Wenzel; Pascal Friederich (CoRR, 2021)

Implementing graph neural networks with TensorFlow-Keras. - Patrick Reiser; André Eberhard; Pascal Friederich (CoRR, 2021)

Graph neural networks in TensorFlow-Keras with RaggedTensor representation (kgcnn). - Patrick Reiser; André Eberhard; Pascal Friederich (Softw. Impacts, 2021)

Graph neural networks for materials science and chemistry. - Patrick Reiser; Marlen Neubert; André Eberhard; Luca Torresi; Chen Zhou; Chen Shao; Houssam Metni; Clint van Hoesel; Henrik Schopmans; Timo Sommer; Pascal Friederich (CoRR, 2022)

MEGAN: Multi-explanation Graph Attention Network. - Jonas Teufel; Luca Torresi; Patrick Reiser; Pascal Friederich (xAI (2), 2023)

Connectivity Optimized Nested Graph Networks for Crystal Structures. - Robin Ruff; Patrick Reiser; Jan Stühmer; Pascal Friederich (CoRR, 2023)

Neural networks trained on synthetically generated crystals can extract structural information from ICSD powder X-ray diffractograms. - Henrik Schopmans; Patrick Reiser; Pascal Friederich (CoRR, 2023)

Interpretable delta-learning of GW quasiparticle energies from GGA-DFT. - Artem Fediai; Patrick Reiser; Jorge Enrique Olivares Peña; Wolfgang Wenzel; Pascal Friederich (Mach. Learn. Sci. Technol., 2023)