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We develop a martingale approximation framework yielding quantitative maximal large deviations estimates for invertible dynamical systems. From suitable decay of correlations, we deduce these estimates and, as an application, we obtain…

Dynamical Systems · Mathematics 2026-05-08 José F. Alves , João S. Matias , Ian Melbourne

This paper deals with analytic families of holomorphic iterated function systems. Using real analyticity of the pressure function (which we prove), we establish a classification theorem for analytic families of holomorphic iterated function…

Dynamical Systems · Mathematics 2009-11-13 Mario Roy , Hiroki Sumi , Mariusz Urbanski

We extend the use of random evolving sets to time-varying conductance models and utilize it to provide tight heat kernel upper bounds. It yields the transience of any uniformly lazy random walk, on Z^d, d>=3, equipped with uniformly bounded…

Probability · Mathematics 2016-03-22 Amir Dembo , Ruojun Huang , Ben Morris , Yuval Peres

We give an elementary proof of a generalization of Rokhlin's lemma for commuting non-invertible measure-preserving transformations, and we present several combinatorial applications.

Dynamical Systems · Mathematics 2016-01-29 Artur Avila , Pablo Candela

We study instabilities and pattern formation in reaction-diffusion layers that are diffusively coupled. For two-layer systems of identical two-component reactions, we analyze the stability of homogeneous steady states by exploiting the…

Pattern Formation and Solitons · Physics 2015-06-03 Anne J. Catlla , Amelia McNamara , Chad M. Topaz

Sequential decision-making algorithms such as reinforcement learning (RL) in real-world scenarios inevitably face environments with partial observability. This paper scrutinizes the effectiveness of a popular architecture, namely…

Machine Learning · Computer Science 2024-05-31 Chenhao Lu , Ruizhe Shi , Yuyao Liu , Kaizhe Hu , Simon S. Du , Huazhe Xu

In this note we construct a canonical lifting of arbitrary Poisson structures on a manifold to its algbera of densities. Using this construction we proceed to classify all extensions of a fixed structure on the original manifold to its…

Mathematical Physics · Physics 2015-06-16 A. Biggs

Recurrent Neural Networks (RNNs) are very successful at solving challenging problems with sequential data. However, this observed efficiency is not yet entirely explained by theory. It is known that a certain class of multiplicative RNNs…

Machine Learning · Computer Science 2019-01-31 Valentin Khrulkov , Oleksii Hrinchuk , Ivan Oseledets

In this chapter, we consider a class of discrete dynamical systems defined on the homogeneous space associated with a regular tiling of $\R^N$, whose most familiar example is provided by the $N-$dimensional torus $\T ^N$. It is proved that…

Analysis of PDEs · Mathematics 2010-02-08 Lionel Rosier

We present recurrent transformer networks (RTNs) for obtaining dense correspondences between semantically similar images. Our networks accomplish this through an iterative process of estimating spatial transformations between the input…

Computer Vision and Pattern Recognition · Computer Science 2018-10-30 Seungryong Kim , Stephen Lin , Sangryul Jeon , Dongbo Min , Kwanghoon Sohn

The periodic tiling conjecture asserts that if a region $\Sigma\subset \mathbb R^d$ tiles $\mathbb R^d$ by translations then it admits at least one fully periodic tiling. This conjecture is known to hold in $\mathbb R$, and recently it was…

Combinatorics · Mathematics 2024-09-26 Jaume de Dios Pont , Jan Grebík , Rachel Greenfeld , Jose Madrid

We give several results showing that different discrete structures typically gain certain spanning substructures (in particular, Hamilton cycles) after a modest random perturbation. First, we prove that adding linearly many random edges to…

Combinatorics · Mathematics 2018-03-23 Michael Krivelevich , Matthew Kwan , Benny Sudakov

We prove a general duality theorem for tangle-like dense objects in combinatorial structures such as graphs and matroids. This paper continues, and assumes familiarity with, the theory developed in [6]

Combinatorics · Mathematics 2014-06-17 Reinhard Diestel , Sang-il Oum

This note considers the finite linear independence of coherent systems associated to discrete subgroups. We show by simple arguments that such coherent systems of amenable groups are linearly independent whenever the associated twisted…

Functional Analysis · Mathematics 2024-11-22 Ulrik Enstad , Jordy Timo van Velthoven

Decoherence-free subsystems have been successfully developed as a tool to preserve fragile quantum information against noises. In this letter, we develop a structure theory for decoherence-free subsystems. Based on it, we present an…

Quantum Physics · Physics 2018-02-15 Ji Guan , Yuan Feng , Mingsheng Ying

The number of standard Young tableaux of a fixed shape is famously given by the hook-length formula due to Frame, Robinson and Thrall. A bijective proof of Novelli, Pak and Stoyanovskii relies on a sorting algorithm akin to jeu-de-taquin…

Combinatorics · Mathematics 2014-03-21 Robin Sulzgruber

We prove that the uniform recurrence of morphic sequences is decidable. For this we show that the number of derived sequences of uniformly recurrent morphic sequences is bounded. As a corollary we obtain that uniformly recurrent morphic…

Combinatorics · Mathematics 2012-09-03 Fabien Durand

We show that planar graphs have bounded queue-number, thus proving a conjecture of Heath, Leighton and Rosenberg from 1992. The key to the proof is a new structural tool called layered partitions, and the result that every planar graph has…

Discrete Mathematics · Computer Science 2020-08-11 Vida Dujmović , Gwenaël Joret , Piotr Micek , Pat Morin , Torsten Ueckerdt , David R. Wood

We give a new way to study recursive towers of curves over a finite field, defined from a bottom curve $\Cun$ and a correspondence $\Cdeux$ on $\Cun$.In particular, we study their asymptotic behavior. A close examination of singularities…

Number Theory · Mathematics 2014-03-19 Emmanuel Hallouin , Marc Perret

We extend the recent latent recurrent modeling to sequential input streams. By interleaving fast, recurrent latent updates with self-organizational ability between slow observation updates, our method facilitates the learning of stable…

Machine Learning · Computer Science 2026-04-23 Shota Takashiro , Masanori Koyama , Takeru Miyato , Yusuke Iwasawa , Yutaka Matsuo , Kohei Hayashi