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Counting forbidden patterns in irregularly sampled time series. I. The effects of under-sampling, random depletion, and timing jitter

Chaos (Woodbury, N.Y.), 2016-12, Vol.26 (12)

2016

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Counting forbidden patterns in irregularly sampled time series. II. Reliability in the presence of highly irregular sampling

Chaos (Woodbury, N.Y.), 2016-12, Vol.26 (12)

2016

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Regenerating time series from ordinal networks

Chaos (Woodbury, N.Y.), 2017-03, Vol.27 (3)

2017

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Optimal Shadowing Filter for a Positioning and Tracking Methodology with Limited Information

Sensors (Basel, Switzerland), 2019-02, Vol.19 (4), p.931

2019

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See–saw relationship of the Holocene East Asian–Australian summer monsoon

Nature communications, 2016-09, Vol.7 (1), p.12929-12929, Article 12929

2016

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Modeling Uncertainties for Automated and Connected Vehicles in Mixed Traffic

Journal of advanced transportation, 2024-08, Vol.2024 (1)

2024

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Multiple Sensors Data Integration for Traffic Incident Detection Using the Quadrant Scan

Sensors (Basel, Switzerland), 2022-04, Vol.22 (8), p.2933

2022

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What exactly are the properties of scale-free and other networks?

Europhysics letters, 2013-09, Vol.103 (5), p.58004

2013

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Estimating topological entropy using ordinal partition networks

Physical review. E, 2021-02, Vol.103 (2), Article 022214

2021

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Network representations of attractors for change point detection

Communications physics, 2023-11, Vol.6 (1), p.340-14, Article 340

2023

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Prediction of flow dynamics using point processes

Chaos (Woodbury, N.Y.), 2018-01, Vol.28 (1)

2018

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Cognitive dissonance and introversion effects on opinion dynamics and echo chamber formation

Physica A, 2024-11, Vol.654, p.130130, Article 130130

2024

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Markov modeling via ordinal partitions: An alternative paradigm for network-based time-series analysis

Physical review. E, 2019-12, Vol.100 (6-1), p.062307-062307, Article 062307

2019

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Parameter estimation for Gipps’ car following model in a Bayesian framework

Physica A, 2024-04, Vol.639, p.129671, Article 129671

2024

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Statistical finite elements for misspecified models

Proceedings of the National Academy of Sciences - PNAS, 2021-01, Vol.118 (2), p.1-6

2021

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Low-rank statistical finite elements for scalable model-data synthesis

Journal of computational physics, 2022-08, Vol.463, p.111261, Article 111261

2022

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Selecting embedding delays: An overview of embedding techniques and a new method using persistent homology

Chaos (Woodbury, N.Y.), 2023-03, Vol.33 (3)

2023

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The active selfish herd

Journal of theoretical biology, 2019-06, Vol.471, p.82-90

2019

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Consistency in echo-state networks

Chaos (Woodbury, N.Y.), 2019-02, Vol.29 (2)

2019

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Time lagged ordinal partition networks for capturing dynamics of continuous dynamical systems

Chaos (Woodbury, N.Y.), 2015-05, Vol.25 (5)

2015

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Crisis and stochastic resonance in Shinriki’s circuit

Physica. D, 2008-05, Vol.237 (6), p.859-865

2008

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Grading your models: Assessing dynamics learning of models using persistent homology

Chaos (Woodbury, N.Y.), 2021-12, Vol.31 (12), p.123109

2021

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Modelling and tracking the flight dynamics of flocking pigeons based on real GPS data (small flock)

Ecological modelling, 2017-01, Vol.344, p.62-72

2017

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Erratum to selecting embedding delays: An overview of embedding techniques and a new method using persistent homology [Chaos: Interdiscip. J. Nonlin. Sci. 33(3), 24 (2023)]

Chaos (Woodbury, N.Y.), 2024-09, Vol.34 (9)

2024

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Stochastic modeling of experimental chaotic time series

Physical review letters, 2007-01, Vol.98 (4), p.044102-044102, Article 044102

2007

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Counting forbidden patterns in irregularly sampled time series. I. The effects of under-sampling, random depletion, and timing jitter

Counting forbidden patterns in irregularly sampled time series. II. Reliability in the presence of highly irregular sampling

Regenerating time series from ordinal networks

Optimal Shadowing Filter for a Positioning and Tracking Methodology with Limited Information

See–saw relationship of the Holocene East Asian–Australian summer monsoon

Modeling Uncertainties for Automated and Connected Vehicles in Mixed Traffic

Multiple Sensors Data Integration for Traffic Incident Detection Using the Quadrant Scan

What exactly are the properties of scale-free and other networks?

Estimating topological entropy using ordinal partition networks

Network representations of attractors for change point detection

Prediction of flow dynamics using point processes

Cognitive dissonance and introversion effects on opinion dynamics and echo chamber formation

Markov modeling via ordinal partitions: An alternative paradigm for network-based time-series analysis

Parameter estimation for Gipps’ car following model in a Bayesian framework

Statistical finite elements for misspecified models

Low-rank statistical finite elements for scalable model-data synthesis

Selecting embedding delays: An overview of embedding techniques and a new method using persistent homology

The active selfish herd

Consistency in echo-state networks

Time lagged ordinal partition networks for capturing dynamics of continuous dynamical systems

Crisis and stochastic resonance in Shinriki’s circuit

Grading your models: Assessing dynamics learning of models using persistent homology

Modelling and tracking the flight dynamics of flocking pigeons based on real GPS data (small flock)

Erratum to selecting embedding delays: An overview of embedding techniques and a new method using persistent homology [Chaos: Interdiscip. J. Nonlin. Sci. 33(3), 24 (2023)]

Stochastic modeling of experimental chaotic time series

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