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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Dynamical Bayesian inference of time-evolving interactions: From a pair of coupled oscillators to networks of oscillators
Andrea Duggento, Tomislav Stankovski, P. V. E. McClintock, et al.
Physical Review E (2012) Vol. 86, Iss. 6
Open Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

Networks beyond pairwise interactions: Structure and dynamics
Federico Battiston, Giulia Cencetti, Iacopo Iacopini, et al.
Physics Reports (2020) Vol. 874, pp. 1-92
Open Access | Times Cited: 1127
Surrogate data for hypothesis testing of physical systems
Gemma Lancaster, Dmytro Iatsenko, Aleksandra Pidde, et al.
Physics Reports (2018) Vol. 748, pp. 1-60
Open Access | Times Cited: 368
Coupling functions: Universal insights into dynamical interaction mechanisms
Tomislav Stankovski, Tiago Pereira, P. V. E. McClintock, et al.
Reviews of Modern Physics (2017) Vol. 89, Iss. 4
Open Access | Times Cited: 251
Nonlinear mode decomposition: A noise-robust, adaptive decomposition method
Dmytro Iatsenko, P. V. E. McClintock, Aneta Stefanovska
Physical Review E (2015) Vol. 92, Iss. 3
Open Access | Times Cited: 115
Partial cross mapping eliminates indirect causal influences
Siyang Leng, Huanfei Ma, Jürgen Kurths, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 76
Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction
Xin Li, Qunxi Zhu, Chengli Zhao, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 11
Coupling functions in networks of oscillators
Tomislav Stankovski, Valentina Ticcinelli, P. V. E. McClintock, et al.
New Journal of Physics (2015) Vol. 17, Iss. 3, pp. 035002-035002
Open Access | Times Cited: 78
Chronotaxic Systems: A New Class of Self-Sustained Nonautonomous Oscillators
Yevhen F. Suprunenko, Philip T. Clemson, Aneta Stefanovska
Physical Review Letters (2013) Vol. 111, Iss. 2
Open Access | Times Cited: 73
Discerning non-autonomous dynamics
Philip T. Clemson, Aneta Stefanovska
Physics Reports (2014) Vol. 542, Iss. 4, pp. 297-368
Open Access | Times Cited: 72
Neural Cross-Frequency Coupling Functions
Tomislav Stankovski, Valentina Ticcinelli, P. V. E. McClintock, et al.
Frontiers in Systems Neuroscience (2017) Vol. 11
Open Access | Times Cited: 67
Coherence and Coupling Functions Reveal Microvascular Impairment in Treated Hypertension
Valentina Ticcinelli, Tomislav Stankovski, Dmytro Iatsenko, et al.
Frontiers in Physiology (2017) Vol. 8
Open Access | Times Cited: 65
Reconstructing Time-Dependent Dynamics
Philip T. Clemson, Gemma Lancaster, Aneta Stefanovska
Proceedings of the IEEE (2016) Vol. 104, Iss. 2, pp. 223-241
Open Access | Times Cited: 54
Setting of the Poincaré section for accurately calculating the phase of rhythmic spatiotemporal dynamics
Takahiro Arai, Yoji Kawamura, Toshio Aoyagi
Physical review. E (2025) Vol. 111, Iss. 1
Open Access
Enhancing cardiovascular monitoring: a non-linear model for characterizing RR interval fluctuations in exercise and recovery
Matías Castillo-Aguilar, Diego Mabe-Castro, David Rangel Medina, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A tutorial on time-evolving dynamical Bayesian inference
Tomislav Stankovski, Andrea Duggento, P. V. E. McClintock, et al.
The European Physical Journal Special Topics (2014) Vol. 223, Iss. 13, pp. 2685-2703
Open Access | Times Cited: 47
Coupling Functions Enable Secure Communications
Tomislav Stankovski, P. V. E. McClintock, Aneta Stefanovska
Physical Review X (2014) Vol. 4, Iss. 1
Open Access | Times Cited: 44
Network Physiology of Exercise: Beyond Molecular and Omics Perspectives
Natàlia Balagué, Robert Hristovski, Maricarmen Almarcha, et al.
Sports Medicine - Open (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 21
Can spurious indications for phase synchronization due to superimposed signals be avoided?
Stephan Porz, Matthäus Kiel, Klaus Lehnertz
Chaos An Interdisciplinary Journal of Nonlinear Science (2014) Vol. 24, Iss. 3
Open Access | Times Cited: 40
Extensions to a manifold learning framework for time-series analysis on dynamic manifolds in bioelectric signals
Burak Erem, R. Martinez Orellana, Damon E. Hyde, et al.
Physical review. E (2016) Vol. 93, Iss. 4
Open Access | Times Cited: 26
Reconstruction of a random phase dynamics network from observations
Arkady Pikovsky
Physics Letters A (2017) Vol. 382, Iss. 4, pp. 147-152
Open Access | Times Cited: 25
Inverse approach to chronotaxic systems for single-variable time series
Philip T. Clemson, Yevhen F. Suprunenko, Tomislav Stankovski, et al.
Physical Review E (2014) Vol. 89, Iss. 3
Open Access | Times Cited: 22
A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data
Takayuki Onojima, Takahiro Goto, Hiroaki Mizuhara, et al.
PLoS Computational Biology (2018) Vol. 14, Iss. 1, pp. e1005928-e1005928
Open Access | Times Cited: 22
Discussion of “Time-frequency Techniques in Biomedical Signal Analysis: A Tutorial Review of Similarities and Differences”
Christian Baumgärtner, Katarzyna J. Blinowska, Andrzej Cichocki, et al.
Methods of Information in Medicine (2013) Vol. 52, Iss. 04, pp. 297-307
Open Access | Times Cited: 20
Dynamical inference: Where phase synchronization and generalized synchronization meet
Tomislav Stankovski, P. V. E. McClintock, Aneta Stefanovska
Physical Review E (2014) Vol. 89, Iss. 6
Open Access | Times Cited: 20
Detecting triplet locking by triplet synchronization indices
Björn Kralemann, Arkady Pikovsky, Michael Rosenblum
Physical Review E (2013) Vol. 87, Iss. 5
Closed Access | Times Cited: 20
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