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Most instruments - formalisms, concepts, and metrics - for social networks analysis fail to capture their dynamics. Typical systems exhibit different scales of dynamics, ranging from the fine-grain dynamics of interactions (which recently…

Social and Information Networks · Computer Science 2011-02-04 Nicola Santoro , Walter Quattrociocchi , Paola Flocchini , Arnaud Casteigts , Frederic Amblard

There are many methods for projecting spherical maps onto the plane. Interactive versions of these projections allow the user to centre the region of interest. However, the effects of such interaction have not previously been evaluated. In…

Human-Computer Interaction · Computer Science 2022-02-23 Kun-Ting Chen , Tim Dwyer , Yalong Yang , Benjamin Bach , Kim Marriott

We investigate the relative merit of phase-based methods---mean phase coherence, unweighted and weighted phase lag index---for estimating the strength of interactions between dynamical systems from empirical time series which are affected…

Neurons and Cognition · Quantitative Biology 2014-09-16 Stephan Porz , Matthäus Kiel , Klaus Lehnertz

The "critical brain hypothesis" posits that neural circuitry may be tuned close to a "critical point" or "phase transition" -- a boundary between different operating regimes of the circuit. The renormalization group and theory of critical…

Neurons and Cognition · Quantitative Biology 2025-10-30 Braden A. W. Brinkman

The advent of data science has provided an increasing number of challenges with high data complexity. This paper addresses the challenge of space-time data where the spatial domain is not a planar surface, a sphere, or a linear network, but…

Methodology · Statistics 2022-08-09 Emilio Porcu , Philip A. White , Marc G. Genton

Temporal graphs are graphs where the edge set can change in each time step, and the vertex set stays the same. Exploration of temporal graphs whose snapshot in each time step is a connected graph, called connected temporal graphs, has been…

Data Structures and Algorithms · Computer Science 2024-07-19 Konstantinos Dogeas , Thomas Erlebach , Frank Kammer , Johannes Meintrup , William K. Moses

We present the mathematical basis of a new approach to the analysis of temporal coding. The foundation of the approach is the construction of several families of novel distances (metrics) between neuronal impulse trains. In contrast to most…

Neurons and Cognition · Quantitative Biology 2007-05-23 Jonathan D. Victor , Keith P. Purpura

Crystalline assemblages of identical sub-units packed together and elastically bent in the form of a torus have been found in the past ten years in a variety of systems of surprisingly different nature, such as viral capsids, self-assembled…

Soft Condensed Matter · Physics 2008-07-29 Luca Giomi , Mark J. Bowick

This work revisits the Euclidean Dynamical Triangulation (DT) approach to non-perturbative quantum gravity in three dimensions. Inspired by a recent combinatorial study by T. Budd and L. Lionni of a subclass of 3-sphere triangulations…

High Energy Physics - Lattice · Physics 2025-09-26 Timothy Budd , Dániel Németh

The various human brain tasks are performed at different locations and time scales. Yet, we discovered the existence of time-invariant (above an essential time scale) partitioning of the brain activity into personal state-specific frequency…

Medical Physics · Physics 2009-11-11 Itai Doron , Eyal Hulata , Itay Baruchi , Vernon L. Towle , Eshel Ben-Jacob

We present a comparative study on Explosive Synchronization (ES) in temporal networks consisting of phase oscillators. The temporal nature of the networks is modeled with two configurations: (1) oscillators are allowed to move in a closed…

Adaptation and Self-Organizing Systems · Physics 2021-02-03 Tanu Singla , M. Rivera

We consider robust estimation of wrapped models to multivariate circular data that are points on the surface of a $p$-torus based on the weighted likelihood methodology.Robust model fitting is achieved by a set of weighted likelihood…

Methodology · Statistics 2024-01-10 Claudio Agostinelli , Luca Greco , Giovanni Saraceno

Biological and social systems consist of myriad interacting units. The interactions can be represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides…

Machine Learning · Statistics 2017-10-25 Norbert Binkiewicz , Joshua T. Vogelstein , Karl Rohe

We demonstrate in numerical experiments that estimators of strength and directionality of coupling between oscillators based on modeling of their phase dynamics [D.A. Smirnov and B.P. Bezruchko, Phys. Rev. E 68, 046209 (2003)] are widely…

Data Analysis, Statistics and Probability · Physics 2009-11-11 D. A. Smirnov , M. B. Bodrov , J. L. Perez Velazquez , R. A. Wennberg , B. P. Bezruchko

Ranked data is commonly used in research across many fields of study including medicine, biology, psychology, and economics. One common statistic used for analyzing ranked data is Kendall's {\tau} coefficient, a non-parametric measure of…

Methodology · Statistics 2023-09-04 Nicholas D. Edwards , Enzo de Jong , Stephen T. Ferguson

Loss of cortical integration and changes in the dynamics of electrophysiological brain signals characterize the transition from wakefulness towards unconsciousness. The common mechanism underlying these observations remains unknown. In this…

We propose Moebius maps as a tool to model synchronization phenomena in coupled phase oscillators. Not only does the map provide fast computation of phase synchronization, it also reflects the underlying group structure of the sinusoidally…

Adaptation and Self-Organizing Systems · Physics 2020-08-19 Chen Chris Gong , Ralf Toenjes , Arkady Pikovsky

Our paper gives bounds for the rate of convergence for a class of random walks on the d-dimensional torus generated by a set of n vectors in R^d/Z^d. We give bounds on the discrepancy distance from Haar measure; our lower bound holds for…

Probability · Mathematics 2007-05-23 Timothy Prescott , Francis Edward Su

Mapping complex input data into suitable lower dimensional manifolds is a common procedure in machine learning. This step is beneficial mainly for two reasons: (1) it reduces the data dimensionality and (2) it provides a new data…

Machine Learning · Computer Science 2018-11-28 Daniele Zambon , Lorenzo Livi , Cesare Alippi

Sufficient conditions for synchronization of coupled Lienard-type oscillators are investigated via averaging technique. Coupling considered here is pairwise, unidirectional, and described by a nonlinear function (whose graph resides in the…

Dynamical Systems · Mathematics 2010-03-15 S. Emre Tuna
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