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We investigate the asymptotic behaviour of networks of interacting non-linear Hawkes processes modeling a homogeneous population of neurons in the large population limit. In particular, we prove a functional central limit theorem for the…

Probability · Mathematics 2021-07-06 Sophie Heesen , Wilhelm Stannat

Most existing expressivity theories for neural networks assume exact real arithmetic, whereas practical neural networks are executed under finite-precision floating-point arithmetic with implementation-dependent execution semantics. Recent…

Machine Learning · Computer Science 2026-05-28 Yeachan Park , Geonho Hwang , Wonyeol Lee , Sejun Park

The solution to the BFKL equation grows like a power of center of mass energy, s, violating unitarity conditions at high energies. The growth of the cross section can be tamed by taking into account multiple pomeron exchanges. This is known…

High Energy Physics - Phenomenology · Physics 2007-05-23 Emil Avsar

We consider time-harmonic incompressible flow with a spatially resolved complex viscosity field $\mu^*(\mathbf{x},\omega)$ and, at fixed forcing frequency $\omega>0$, its constitutive phase texture…

Analysis of PDEs · Mathematics 2026-01-19 Lillian St. Kleess

This paper aims to understand the training solution, which is obtained by the back-propagation algorithm, of two-layer neural networks whose hidden layer is composed of the units with smooth activation functions, including the usual sigmoid…

Machine Learning · Computer Science 2025-07-22 Changcun Huang

As modern deep learning architectures grow in complexity, representational ambiguity emerges as a critical barrier to their interpretability and reliable merging. For ReLU networks, identical functional mappings can be achieved through…

Machine Learning · Computer Science 2026-04-21 Kutomanov Hennadii

In this paper, we construct neural networks with ReLU, sine and $2^x$ as activation functions. For general continuous $f$ defined on $[0,1]^d$ with continuity modulus $\omega_f(\cdot)$, we construct ReLU-sine-$2^x$ networks that enjoy an…

Machine Learning · Computer Science 2022-08-16 Yuling Jiao , Yanming Lai , Xiliang Lu , Fengru Wang , Jerry Zhijian Yang , Yuanyuan Yang

The $f^{-\gamma}$ sloped current noise power spectra, observed in organic semiconductors, have been interpreted within a {\em variable range hopping} mechanism of the fluctuations. The relative current noise power spectral density ${\cal…

Disordered Systems and Neural Networks · Physics 2009-03-20 A. Carbone , B. K. Kotowska , D. Kotowski

Our aim in this paper is twofold. Firstly, we develop a new asymptotic theory for Floquet exponents. We consider a linear system of differential equations with a time-periodic coefficient matrix. Assuming that the coefficient matrix depends…

Analysis of PDEs · Mathematics 2021-10-18 Habib Ammari , Erik Orvehed Hiltunen , Thea Kosche

We study Schr\"odinger operators with Floquet boundary conditions on flat tori obtaining a spectral result giving an asymptotic expansion of all the eigenvalues. The expansion is in $\lambda^{-\delta}$ with $\delta\in(0,1)$ for most of the…

Mathematical Physics · Physics 2021-09-22 Dario Bambusi , Beatrice Langella , Riccardo Montalto

The effect of structural constriction on molecular mobility is investigated by broadband dielectric spectroscopy (BDS) within three types of molecular arrangements: monomers, oligomers and self-assembled monolayers (SAMs). While disordered…

We consider the self-energy and quasiparticle spectrum, for both electrons interacting with phonons, and composite fermions interacting with gauge fluctuations. In both cases we incorporate the singular structure arising from Landau level…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 S. Curnoe , P. C. E. Stamp

We theoretically studied the Floquet state of gated bilayer graphene, which is irradiated by normally incident focused Gaussian beam with orbital angular momentum (OAM). According to the Floquet theory, in-plane and out-of-plane electric…

Mesoscale and Nanoscale Physics · Physics 2024-04-02 Ma Luo

We consider the capacity of \emph{treelike committee machines} (TCM) neural networks. Relying on Random Duality Theory (RDT), \cite{Stojnictcmspnncaprdt23} recently introduced a generic framework for their capacity analysis. An upgrade…

Machine Learning · Statistics 2024-02-09 Mihailo Stojnic

We investigate the excitation spectrum of strongly correlated sodium cobaltate within a realistic many-body description beyond dynamical mean-field theory (DMFT). At lower doping around $x$=0.3, rather close to Mott-critical half-filling,…

Strongly Correlated Electrons · Physics 2015-04-16 Aljoscha Wilhelm , Frank Lechermann , Hartmut Hafermann , Mikhail I. Katsnelson , Alexander I. Lichtenstein

In this paper, we report the excitation of coherent density and potential fluctuations induced by magnetohydrodynamic (MHD) activity in the edge plasma region of ADITYA-U Tokamak. When the amplitude of the MHD mode, mainly the m/n = 2/1,…

The $1/f$-like decay observed in the power spectrum of electro-physiological signals, along with scale-free statistics of the so-called neuronal avalanches, constitute evidences of criticality in neuronal systems. Recent in vitro studies…

Neurons and Cognition · Quantitative Biology 2017-08-31 Fabrizio Lombardi , Hans J. Herrmann , Lucilla de Arcangelis

We study the approximation properties of shallow neural networks with an activation function which is a power of the rectified linear unit. Specifically, we consider the dependence of the approximation rate on the dimension and the…

Numerical Analysis · Mathematics 2021-12-23 Jonathan W. Siegel , Jinchao Xu

In the previous work hep-ph/0112140, hep-ph/0204277, we showed that while the nonlinear QCD evolution equation of Balitsky and Kovchegov (BK) leads to saturation of the scattering amplitude locally in impact parameter space, it does not…

High Energy Physics - Phenomenology · Physics 2009-11-07 Alexander Kovner , Urs Achim Wiedemann

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural…

Neurons and Cognition · Quantitative Biology 2020-02-27 Gabriel Koch Ocker , Krešimir Josić , Eric Shea-Brown , Michael A. Buice
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