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Due to the over-smoothing issue, most existing graph neural networks can only capture limited dependencies with their inherently finite aggregation layers. To overcome this limitation, we propose a new kind of graph convolution, called…

Machine Learning · Computer Science 2022-06-30 Qi Chen , Yifei Wang , Yisen Wang , Jiansheng Yang , Zhouchen Lin

In this paper the evolution of a binary mixture in a thin-film geometry with a wall at the top and bottom is considered. By bringing the mixture into its miscibility gap so that no spinodal decomposition occurs in the bulk, a slight…

We consider Glauber dynamics of classical spin systems of Ising type in the limit when the temperature tends to zero in finite volume. We show that information on the structure of the most profound minima and the connecting saddle points of…

Disordered Systems and Neural Networks · Physics 2015-06-24 Anton Bovier , Francesco Manzo

This paper proposes four new methods to decontaminate spectra of stars and galaxies resulting from slitless spectroscopy used in many space missions such as Euclid. These methods are based on two distinct approaches and simultaneously take…

Instrumentation and Methods for Astrophysics · Physics 2026-02-11 Mostafa Bella , Shahram Hosseini , Thierry Contini , Hicham Saylani

P-splines provide a flexible setting for modeling nonlinear model components based on a discretized penalty structure with a relatively simple computational backbone. Under a Bayesian inferential framework based on Markov chain Monte Carlo,…

Methodology · Statistics 2025-11-03 Oswaldo Gressani , Paul H. C. Eilers

We discuss a Statistical Mechanics approach in the manner of Edwards to the ``inherent states'' (defined as the stable configurations in the potential energy landscape) of glassy systems and granular materials. We show that at stationarity…

Statistical Mechanics · Physics 2009-11-07 Annalisa Fierro , Mario Nicodemi , Antonio Coniglio

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee…

Software Engineering · Computer Science 2018-05-10 Roland Kluge , Michael Stein , Gergely Varró , Andy Schürr , Matthias Hollick , Max Mühlhäuser

We consider the most general single-spin-flip dynamics for the ferromagnetic Ising chain with nearest-neighbour influence and spin reversal symmetry. This dynamics is a two-parameter extension of Glauber dynamics corresponding respectively…

Statistical Mechanics · Physics 2015-05-29 C. Godreche , J. -M. Luck

We investigate the maximum caliber variational principle as an inference algorithm used to predict dynamical properties of complex nonequilibrium, stationary, statistical systems in the presence of incomplete information. Specifically, we…

Statistical Mechanics · Physics 2016-12-28 Carlo Cafaro , Sean Alan Ali

A class of robust estimators of scatter applied to information-plus-impulsive noise samples is studied, where the sample information matrix is assumed of low rank; this generalizes the study of (Couillet et al., 2013b) to spiked random…

Probability · Mathematics 2014-05-01 Romain Couillet

This article is in the spirit of our work on the consequences of the Regge calculus, where some edge length scale arises as an optimal initial point of the perturbative expansion after functional integration over connection. Now consider…

General Relativity and Quantum Cosmology · Physics 2024-01-03 V. M. Khatsymovsky

The conventional no-slip boundary condition leads to a non-integrable stress singularity at a moving contact line. This makes numerical simulations challenging, especially when capillary effects are essential for the dynamics of the flow.…

Fluid Dynamics · Physics 2017-09-18 Hanna Holmgren , Gunilla Kreiss

We consider the symmetric inclusion process on a general finite graph. Our main result establishes universal upper and lower bounds for the spectral gap of this interacting particle system in terms of the spectral gap of the random walk on…

Probability · Mathematics 2025-12-09 Seonwoo Kim , Federico Sau

The performance of mobile edge computing (MEC) depends critically on the quality of the wireless channels. From this viewpoint, the recently advocated intelligent reflecting surface (IRS) technique that can proactively reconfigure wireless…

Information Theory · Computer Science 2021-02-10 Huilian Zhang , Xiaofan He , Qingqing Wu , Huaiyu Dai

We introduce some applications of Stein's method in the high temperature analysis of spin glasses. Stein's method allows the direct analysis of the Gibbs measure without having to create a cavity. Another advantage is that it gives limit…

Probability · Mathematics 2009-08-02 Sourav Chatterjee

Let $\lambda_{1}(G)$ and $\mu_{1}(G)$ denote the spectral radius and the Laplacian spectral radius of a graph $G$, respectively. Li in [Electronic J. Linear Algebra 34 (2018) 389-392] proved sharp upper bounds of $\lambda_{1}(G)$ based on…

Combinatorics · Mathematics 2018-09-06 Huicai Jia , Ruifang Liu , Hong-Jian Lai

Context. Recently our ability to study stars using asteroseismic techniques has increased dramatically, largely through the use of space based photometric observations. Work has also been done using ground based spectroscopic observations…

Solar and Stellar Astrophysics · Physics 2018-10-03 Jesper Schou

We consider spin systems on the integer lattice graph $\mathbb{Z}^d$ with nearest-neighbor interactions. We develop a combinatorial framework for establishing that exponential decay with distance of spin correlations, specifically the…

Discrete Mathematics · Computer Science 2017-08-09 Antonio Blanca , Pietro Caputo , Alistair Sinclair , Eric Vigoda

Motivated by multi-topology building and city model data, first a lossless representation of multiple $T_0$-topologies on a given finite set by a vertex-edge-weighted graph is given, and the subdominant ultrametric of the associated…

Discrete Mathematics · Computer Science 2024-11-05 Patrick Erik Bradley , Angel Alfredo Moran Ledezma

The inadequate mixing of conventional Markov Chain Monte Carlo (MCMC) methods for multi-modal distributions presents a significant challenge in practical applications such as Bayesian inference and molecular dynamics. Addressing this, we…

Machine Learning · Statistics 2024-05-30 Wenlin Chen , Mingtian Zhang , Brooks Paige , José Miguel Hernández-Lobato , David Barber
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