Matrix-based representation for coordination fault detection: a formal approach. - Meir Kalech; Michael Lindner; Gal A. Kaminka (AAMAS, 2007)

The neural substrates of person comparison - An fMRI study. - Michael Lindner; Tanja Hundhammer; Angela Ciaramidaro; David E. J. Linden; Thomas Mussweiler (NeuroImage, 2008)

A representation for coordination fault detection in large-scale multi-agent systems. - Michael Lindner; Meir Kalech; Gal A. Kaminka (Ann. Math. Artif. Intell., 2009)

Transfer entropy - a model-free measure of effective connectivity for the neurosciences. - Raul Vicente; Michael Wibral; Michael Lindner; Gordon Pipa (J. Comput. Neurosci., 2011)

NetworkDynamics.jl - Composing and simulating complex networks in Julia. - Michael Lindner; Lucas Lincoln; Fenja Drauschke; Julia Monika Koulen; Hans Würfel; Anton Plietzsch; Frank Hellmann (CoRR, 2020)

Predicting Dynamic Stability of Power Grids using Graph Neural Networks. - Christian Nauck; Michael Lindner; Konstantin Schürholt; Haoming Zhang; Paul Schultz; Jürgen Kurths; Ingrid Isenhardt; Frank Hellmann (CoRR, 2021)

An Open Source Software Stack for Tuning the Dynamical Behavior of Complex Power Systems. - Anna Büttner; Hans Würfel; Anton Plietzsch; Michael Lindner; Frank Hellmann (OSMSES, 2022)

Dynamic stability of power grids - new datasets for Graph Neural Networks. - Christian Nauck; Michael Lindner; Konstantin Schürholt; Frank Hellmann (CoRR, 2022)

Towards dynamic stability analysis of sustainable power grids using graph neural networks. - Christian Nauck; Michael Lindner; Konstantin Schürholt; Frank Hellmann (CoRR, 2022)

Information-theoretic analyses of neural data to minimize the effect of researchers' assumptions in predictive coding studies. - Patricia Wollstadt; Daniel L. Rathbun; W. Martin Usrey; André Moraes Bastos; Michael Lindner; Viola Priesemann; Michael Wibral (PLoS Comput. Biol., 2023)

Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning. - Christian Nauck; Michael Lindner; Nora Molkenthin; Jürgen Kurths; Eckehard Schöll; Jörg Raisch; Frank Hellmann (CoRR, 2024)

Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning. - Christian Nauck; Anna Büttner; Sebastian Liemann; Frank Hellmann; Michael Lindner (CoRR, 2024)

Dirac-Bianconi Graph Neural Networks - Enabling Non-Diffusive Long-Range Graph Predictions. - Christian Nauck; Rohan Gorantla; Michael Lindner; Konstantin Schürholt; Antonia S. J. S. Mey; Frank Hellmann (CoRR, 2024)