English
Related papers

Related papers: Interdependent scaling exponents in the human brai…

200 papers

By means of the concept of balanced estimation of diffusion entropy we evaluate reliable scale-invariance embedded in different sleep stages and stride records. Segments corresponding to Wake, light sleep, REM, and deep sleep stages are…

Disordered Systems and Neural Networks · Physics 2012-11-14 Wenqing Zhang , Lu Qiu , Qin Xiao , Huijie Yang , Qingjun Zhang , Jianyong Wang

In the vicinity of the onset of an instability, we investigate the effect of colored multiplicative noise on the scaling of the moments of the unstable mode amplitude. We introduce a family of zero dimensional models for which we can…

Statistical Mechanics · Physics 2015-06-05 Alexandros Alexakis , François Pétrélis

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the…

Data Analysis, Statistics and Probability · Physics 2012-01-10 Stephan Bialonski , Martin Wendler , Klaus Lehnertz

We consider the problem of estimating self-exciting generalized linear models from limited binary observations, where the history of the process serves as the covariate. We analyze the performance of two classes of estimators, namely the…

Neural and Evolutionary Computing · Computer Science 2017-03-24 Abbas Kazemipour , Min Wu , Behtash Babadi

The exponential scaling of isotopic yields is investigated for sources of different sizes over a broad range of excitation energies and freeze-out volumes, in both primary and asymptotic stages of the decay in the framework of a…

Nuclear Theory · Physics 2007-05-23 Ad. R. Raduta

Deep ResNets are recognized for achieving state-of-the-art results in complex machine learning tasks. However, the remarkable performance of these architectures relies on a training procedure that needs to be carefully crafted to avoid…

Machine Learning · Computer Science 2025-03-04 Pierre Marion , Adeline Fermanian , Gérard Biau , Jean-Philippe Vert

Scale-invariance is a ubiquitous observation in the dynamics of large distributed complex systems. The computation of its scaling exponents, which provide clues on its origin, is often hampered by the limited available sampling data, making…

The estimation of sparse hierarchical components reflecting patterns of the brain's functional connectivity from rsfMRI data can contribute to our understanding of the brain's functional organization, and can lead to biomarkers of diseases.…

Machine Learning · Computer Science 2021-04-22 Dushyant Sahoo , Christos Davatzikos

n this paper we consider polynomial cointegrating relationships among stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we consider a form of spectral regression around…

Statistics Theory · Mathematics 2008-06-06 Marco Avarucci , Domenico Marinucci

We describe a chain of unidirectionally coupled adaptive excitable elements slowly driven by a stochastic process from one end and open at the other end, as a minimal toy model of unresolved irreducible uncertainty in a system performing…

Neurons and Cognition · Quantitative Biology 2022-09-14 Mario Martinez-Saito

The desirability of evaluating the effective potential in field theories near a phase transition has been recognized in a number of different areas. We show that recent Monte Carlo simulations for the probability distribution for the order…

Statistical Mechanics · Physics 2011-05-12 Joseph Rudnick , William Lay , David Jasnow

We analyze the renormalization of systems whose effective degrees of freedom are described in terms of fluctuations which are ``environment'' dependent. Relevant environmental parameters considered are: temperature, system size, boundary…

High Energy Physics - Theory · Physics 2015-06-26 Denjoe O'Connor , C. R. Stephens

Covariance matrix of heights measured relative to the average height of a growing self-affine surface in the steady state are investigated in the framework of random matrix theory. We show that the spectral density of the covariance matrix…

Statistical Mechanics · Physics 2015-06-11 Hyun-Joo Kim , Doil Jung

The scaling of the thermoremanent magnetization and of the dissipative part of the non-equilibrium magnetic susceptibility is analysed as a function of the waiting-time $s$ for a simple ferromagnet undergoing phase-ordering kinetics after a…

Condensed Matter · Physics 2009-11-07 Malte Henkel , Matthias Paessens , Michel Pleimling

Human reasoning is shaped by resource rationality -- optimizing performance under constraints. Recently, inference-time scaling has emerged as a powerful paradigm to improve the reasoning performance of Large Language Models by expanding…

Computation and Language · Computer Science 2026-02-12 Zhimin Hu , Riya Roshan , Sashank Varma

Perturbative expansions in many physical systems yield 'only' asymptotic series which are not even Borel resummable. Interestingly, the corresponding ambiguities point to nonperturbative physics. We numerically verify this renormalon…

High Energy Physics - Lattice · Physics 2020-11-03 Falk Bruckmann , Matthias Puhr

The Wilsonian renormalisation group is applied to a system of two nonrelativistic particles interacting via short-range forces and coupled to an external EM field. By demanding that a fully off-shell one-particle-irreducible 5-point…

Nuclear Theory · Physics 2019-01-30 A. N. Kvinikhidze , M. C. Birse

In this paper, we address the logarithmic corrections to the leading power laws that govern thermodynamic quantities as a second-order phase transition point is approached. For phase transitions of spin systems on d-dimensional lattices,…

Statistical Mechanics · Physics 2015-07-02 V. Palchykov , C. von Ferber , R. Folk , Yu. Holovatch , R. Kenna

Topology and many-body localization (MBL) have opened new avenues for preserving quantum information at finite energy density. Resonant delocalization plays a crucial role in destabilizing these phenomena. In this work, we study the…

Disordered Systems and Neural Networks · Physics 2023-09-26 Jared Jeyaretnam , Christopher J. Turner , Arijeet Pal

Turbulence is known to show intermittency. That is, statistical properties vary with the length scale in a way not accounted for by statistical similarity where dimensionless ratios of moments are constant. Intermittency occurs even in the…

Fluid Dynamics · Physics 2007-05-23 Mogens V. Melander , Bruce R. Fabijonas