Search Results for author: Jürgen Kurths

Found 17 papers, 9 papers with code

Predicting Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning

1 code implementation27 Feb 2024 Christian Nauck, Michael Lindner, Nora Molkenthin, Jürgen Kurths, Eckehard Schöll, Jörg Raisch, Frank Hellmann

A functional property that is of theoretical and practical interest for oscillatory systems is the stability of synchrony to localized perturbations.

Embedding Theory of Reservoir Computing and Reducing Reservoir Network Using Time Delays

no code implementations16 Mar 2023 Xing-Yue Duan, Xiong Ying, Si-Yang Leng, Jürgen Kurths, Wei Lin, Huan-Fei Ma

Reservoir computing (RC), a particular form of recurrent neural network, is under explosive development due to its exceptional efficacy and high performance in reconstruction or/and prediction of complex physical systems.

Symbiosis of an artificial neural network and models of biological neurons: training and testing

no code implementations3 Feb 2023 Tatyana Bogatenko, Konstantin Sergeev, Andrei Slepnev, Jürgen Kurths, Nadezhda Semenova

In this paper we show the possibility of creating and identifying the features of an artificial neural network (ANN) which consists of mathematical models of biological neurons.

PrEF: Percolation-based Evolutionary Framework for the diffusion-source-localization problem in large networks

no code implementations16 May 2022 Yang Liu, Xiaoqi Wang, Xi Wang, Zhen Wang, Jürgen Kurths

We assume that the state of a number of nodes in a network could be investigated if necessary, and study what configuration of those nodes could facilitate a better solution for the diffusion-source-localization (DSL) problem.

Predicting Basin Stability of Power Grids using Graph Neural Networks

1 code implementation18 Aug 2021 Christian Nauck, Michael Lindner, Konstantin Schürholt, Haoming Zhang, Paul Schultz, Jürgen Kurths, Ingrid Isenhardt, Frank Hellmann

We investigate the feasibility of applying graph neural networks (GNN) to predict dynamic stability of synchronisation in complex power grids using the single-node basin stability (SNBS) as a measure.

Anticipation-induced social tipping -- Can the environment be stabilised by social dynamics?

no code implementations3 Dec 2020 Paul Manuel Müller, Jobst Heitzig, Jürgen Kurths, Kathy Lüdge, Marc Wiedermann

Acknowledging that societies have the additional capability for foresight, this work proposes a conceptual feedback model of socio-ecological co-evolution with the specific construct of anticipation acting as a mediator between the social and natural system.

Physics and Society

Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency

no code implementations29 Nov 2020 Chongzhen Zhang, Yang Tang, Chaoqiang Zhao, Qiyu Sun, Zhencheng Ye, Jürgen Kurths

Semantic segmentation and depth completion are two challenging tasks in scene understanding, and they are widely used in robotics and autonomous driving.

Autonomous Driving Depth Completion +3

When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey

no code implementations29 Mar 2020 Chongzhen Zhang, Jianrui Wang, Gary G. Yen, Chaoqiang Zhao, Qiyu Sun, Yang Tang, Feng Qian, Jürgen Kurths

Then, we further review the performance of RL and meta-learning from the aspects of accuracy or transferability or both of them in autonomous systems, involving pedestrian tracking, robot navigation and robotic manipulation.

Deblurring Decision Making +12

Delay master stability of inertial oscillator networks

1 code implementation21 Nov 2019 Reyk Börner, Paul Schultz, Benjamin Ünzelmann, Deli Wang, Frank Hellmann, Jürgen Kurths

Time lags occur in a vast range of real-world dynamical systems due to finite reaction times or propagation speeds.

Dynamical Systems Adaptation and Self-Organizing Systems

Machine Discovery of Partial Differential Equations from Spatiotemporal Data

1 code implementation15 Sep 2019 Ye Yuan, Junlin Li, Liang Li, Frank Jiang, Xiuchuan Tang, Fumin Zhang, Sheng Liu, Jorge Goncalves, Henning U. Voss, Xiuting Li, Jürgen Kurths, Han Ding

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data.

Deterministic limit of temporal difference reinforcement learning for stochastic games

1 code implementation19 Sep 2018 Wolfram Barfuss, Jonathan F. Donges, Jürgen Kurths

Reinforcement learning in multi-agent systems has been studied in the fields of economic game theory, artificial intelligence and statistical physics by developing an analytical understanding of the learning dynamics (often in relation to the replicator dynamics of evolutionary game theory).

Multiagent Systems

Operationalization of Topology of Sustainable Management to Estimate Qualitatively Different Regions in State Space

2 code implementations8 Jun 2017 Tim Kittel, Rebekka Koch, Jobst Heitzig, Guillaume Deffuant, Jean-Denis Mathias, Jürgen Kurths

To apply the framework of Topology of Sustainable Management (TSM) by Heitzig et al. (2016) to dynamical models, we connect it to viability theory (VT) via a variant definition of the former.

Optimization and Control

Deep Graphs - a general framework to represent and analyze heterogeneous complex systems across scales

1 code implementation4 Apr 2016 Dominik Traxl, Niklas Boers, Jürgen Kurths

These include, most importantly, an explicit association of information with possibly heterogeneous types of objects and relations, and a conclusive representation of the properties of groups of nodes as well as the interactions between such groups on different scales.

Data Analysis, Statistics and Probability Social and Information Networks Atmospheric and Oceanic Physics Physics and Society

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

1 code implementation2 Jul 2015 Jonathan F. Donges, Jobst Heitzig, Boyan Beronov, Marc Wiedermann, Jakob Runge, Qing Yi Feng, Liubov Tupikina, Veronika Stolbova, Reik V. Donner, Norbert Marwan, Henk A. Dijkstra, Jürgen Kurths

Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series.

Data Analysis, Statistics and Probability Atmospheric and Oceanic Physics

Optimal model-free prediction from multivariate time series

no code implementations18 Jun 2015 Jakob Runge, Reik V. Donner, Jürgen Kurths

Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal pre-selection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable.

Time Series Time Series Analysis

Macroscopic description of complex adaptive networks co-evolving with dynamic node states

2 code implementations19 Mar 2015 Marc Wiedermann, Jonathan F. Donges, Jobst Heitzig, Wolfgang Lucht, Jürgen Kurths

In many real-world complex systems, the time-evolution of the network's structure and the dynamic state of its nodes are closely entangled.

Physics and Society

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