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Michael Lindner
Michael Lindner
PostDoc Technische Universität Berlin
Bestätigte E-Mail-Adresse bei pik-potsdam.de
Titel
Zitiert von
Zitiert von
Jahr
Predicting basin stability of power grids using graph neural networks
C Nauck, M Lindner, K Schürholt, H Zhang, P Schultz, J Kurths, I Isenhardt, ...
New Journal of Physics 24 (4), 043041, 2022
402022
Stochastic basins of attraction and generalized committor functions
M Lindner, F Hellmann
Physical Review E 100 (2), 022124, 2019
332019
Spatio-temporal organization of dynamics in a two-dimensional periodically driven vortex flow: A Lagrangian flow network perspective
M Lindner, RV Donner
Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (3), 2017
232017
NetworkDynamics. jl—Composing and simulating complex networks in Julia
M Lindner, L Lincoln, F Drauschke, JM Koulen, H Würfel, A Plietzsch, ...
Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (6), 2021
222021
Characterizing flows by complex network methods
RV Donner, M Lindner, L Tupikina, N Molkenthin
A mathematical modeling approach from nonlinear dynamics to complex systems …, 2019
182019
Toward dynamic stability assessment of power grid topologies using graph neural networks
C Nauck, M Lindner, K Schürholt, F Hellmann
Chaos: An Interdisciplinary Journal of Nonlinear Science 33 (10), 2023
16*2023
Whose house is on fire? Identifying socio-demographic and housing characteristics driving differences in the UK household CO2 emissions
A Schuster, M Lindner, IM Otto
Ecological Economics 207, 107764, 2023
92023
Ecology and Class Structure: Greenhouse Gas Emissions of Social Classes in the United Kingdom
M Lindner, R Dorschel, A Schuster
Available at SSRN 4291462, 2022
62022
Dirac-Bianconi Graph Neural Networks–Enabling Non-Diffusive Long-Range Graph Predictions
C Nauck, R Gorantla, M Lindner, K Schürholt, ASJS Mey, F Hellmann
ICML 2024 Workshop on Geometry-grounded Representation Learning and …, 0
4*
An open source software stack for tuning the dynamical behavior of complex power systems
A Büttner, H Würfel, A Plietzsch, M Lindner, F Hellmann
2022 Open Source Modelling and Simulation of Energy Systems (OSMSES), 1-6, 2022
32022
Applying modeling, simulation and machine learning for the renewable energy transition
M Lindner
PQDT-Global, 2023
22023
Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning
C Nauck, A Büttner, S Liemann, F Hellmann, M Lindner
arXiv preprint arXiv:2406.08917, 2024
12024
Modeling brain network flexibility in networks of coupled oscillators: a feasibility study
N Chinichian, M Lindner, S Yanchuk, T Schwalger, E Schöll, R Berner
Scientific Reports 14 (1), 5713, 2024
12024
Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning
C Nauck, M Lindner, N Molkenthin, J Kurths, E Schöll, J Raisch, ...
arXiv preprint arXiv:2402.17500, 2024
12024
Towards predicting dynamic stability of power grids with Graph Neural Networks
C Nauck, M Lindner, K Schürholt, F Hellmann
12023
NetworkDynamics. jl
M Lindner, H Würfel, F Hellmann
CERN/Zenodo, 2025
2025
AmbientForcing. jl
A Büttner, M Lindner
CERN/Zenodo, 2024
2024
Paper companion: Towards dynamic stability analysis of sustainable power grids using graph neural networks (Neurips Workshop Climate Change AI)
C Nauck, M Lindner, K Schürholt, F Hellmann
CERN/Zenodo, 2022
2022
Dynamic stability of power grids-new datasets for Graph Neural Networks.
C Nauck, M Lindner, K Schürholt, F Hellmann
CoRR, 2022
2022
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