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The $k$-tensor Ising model is an exponential family on a $p$-dimensional binary hypercube for modeling dependent binary data, where the sufficient statistic consists of all $k$-fold products of the observations, and the parameter is an…

Statistics Theory · Mathematics 2023-07-25 Tianyu Liu , Somabha Mukherjee , Rahul Biswas

For nonconvex and nonsmooth restoration models, the lower bound theory reveals their good edge recovery ability, and related analysis can help to design convergent algorithms. Existing such discussions are focused on isotropic…

Numerical Analysis · Mathematics 2021-05-25 Chunlin Wu , Xuan Lin , Yufei Zhao

The study of Markov processes and broadcasting on trees has deep connections to a variety of areas including statistical physics, graphical models, phylogenetic reconstruction, Markov Chain Monte Carlo, and community detection in random…

Probability · Mathematics 2022-10-26 Frederic Koehler , Elchanan Mossel

A recursion technique for the renormalization of semiclassical expansions for the Regge trajectories of bound states of the Schr\"odinger equation is developed. As an application of the proposed technique, the two-parameter renormalization…

Quantum Physics · Physics 2007-05-23 D. A. Kulikov , R. S. Tutik

The problem of reconstructing evolutionary trees or phylogenies is of great interest in computational biology. A popular model for this problem assumes that we are given the set of leaves (current species) of an unknown binary tree and the…

Data Structures and Algorithms · Computer Science 2022-06-16 Eshwar Ram Arunachaleswaran , Anindya De , Sampath Kannan

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima

We present a detailed analysis of the class of regression decision tree algorithms which employ a regulized piecewise-linear node-splitting criterion and have regularized linear models at the leaves. From a theoretic standpoint, based on…

Machine Learning · Computer Science 2019-07-02 Leonidas Lefakis , Oleksandr Zadorozhnyi , Gilles Blanchard

Given an ensemble of randomized regression trees, it is possible to restructure them as a collection of multilayered neural networks with particular connection weights. Following this principle, we reformulate the random forest method of…

Machine Learning · Statistics 2018-04-04 Gérard Biau , Erwan Scornet , Johannes Welbl

Consider a Markov chain on an infinite tree T=(V,E) rooted at \rho. In such a chain, once the initial root state \sigma(\rho) is chosen, each vertex iteratively chooses its state from the one of its parent by an application of a Markov…

Probability · Mathematics 2007-06-13 Svante Janson , Elchanan Mossel

The tree-metric theorem provides a necessary and sufficient condition for a dissimilarity matrix to be a tree metric, and has served as the foundation for numerous distance-based reconstruction methods in phylogenetics. Our main result is…

Combinatorics · Mathematics 2007-05-23 Lior Pachter , David E Speyer

We find a new solution of the renormalization group for the Potts model with ferromagnetic random valued coupling constants. The solution exhibits universality and broken replica symmetry. It is argued that the model reaches this…

High Energy Physics - Theory · Physics 2016-09-06 Viktor Dotsenko , Vladimir Dotsenko , Marco Picco , Pierre Pujol

We present a reconstruction method that stably recovers the real valued, symmetric tensors compactly supported in the Euclidean plane, from knowledge of their attenuated momenta ray transform. The problem is recast as an inverse boundary…

Analysis of PDEs · Mathematics 2024-05-09 Hiroshi Fujiwara , David Omogbhe , Kamran Sadiq , Alexandru Tamasan

We construct multiplicative renormalization for the Epstein--Glaser renormalization scheme in perturbative Algebraic Quantum Field Theory: To this end, we fully combine the Connes--Kreimer renormalization framework with the Epstein--Glaser…

Mathematical Physics · Physics 2025-12-11 Jonah Epstein , Arne Hofmann , David Prinz

We use the generic replica symmetric cubic field-theory to study the transition of short range Ising spin glasses in a magnetic field around the upper critical dimension, d=6. A novel fixed-point is found, in addition to the well-known zero…

Disordered Systems and Neural Networks · Physics 2009-11-07 T. Temesvari , C. De Dominicis

An analysis is made of various methods of phenomenological renormalization based on finite-size scaling equations for inverse correlation lengths, the singular part of the free energy density, and their derivatives. The analysis is made…

Statistical Mechanics · Physics 2009-11-07 M. A. Yurishchev

The two-dimensional Ising model on a distorted Kagom\'{e} lattice is studied by means of exact solutions and the tensor renormalisation group (TRG) method. The zero-field phase diagrams are obtained, where three phases such as…

Statistical Mechanics · Physics 2010-10-27 Wei Li , Shou-Shu Gong , Yang Zhao , Shi-Ju Ran , Song Gao , Gang Su

In this article, we consider a Branching Random Walk on the real line. The genealogical structure is assumed to be given through a supercritical branching process in the i.i.d. environment and satisfies the Kesten-Stigum condition. The…

Probability · Mathematics 2023-02-02 Ayan Bhattacharya , Zbigniew Palmowski

In cross-section-space probability table constructions, reaction-channel levels are reconstructed on fixed total-subgroup nodes and probabilities. Although the standard full-matching reconstruction is uniquely determined, it does not in…

Computational Physics · Physics 2026-04-14 Beichen Zheng , Lili Wen

We review boundary rigidity theorems assessing that, under appropriate conditions, Riemannian manifolds with the same spectrum of boundary geodesics are isometric. We show how to apply these theorems to the problem of reconstructing a $d+1$…

High Energy Physics - Theory · Physics 2009-11-10 M. Porrati , R. Rabadan

We introduce a coarse-graining transformation for tensor networks that can be applied to study both the partition function of a classical statistical system and the Euclidean path integral of a quantum many-body system. The scheme is based…

Strongly Correlated Electrons · Physics 2015-11-04 Glen Evenbly , Guifre Vidal
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