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Algorithms for node clustering typically focus on finding homophilous structure in graphs. That is, they find sets of similar nodes with many edges within, rather than across, the clusters. However, graphs often also exhibit heterophilous…

Machine Learning · Computer Science 2023-08-15 Sudhanshu Chanpuriya , Cameron Musco

A non-abelian generalisation of a theory of gravity coupled to a 2-form gauge field and a dilaton is found, in which the metric and 3-form field strength are Lie algebra-valued. In the abelian limit, the curvature with torsion is self-dual…

High Energy Physics - Theory · Physics 2009-10-30 C. M. Hull

We generalize the non-abelianization of Gaiotto-Moore-Neitzke from the case of $SL(n)$ and $GL(n)$ to arbitrary reductive algebraic groups. This gives a map between a moduli space of certain $N$-shifted weakly $W$-equivariant $T$-local…

Algebraic Geometry · Mathematics 2021-03-24 Matei Ionita , Benedict Morrissey

Motivated by very large-scale communication networks, we newly introduce exponentiation of graphs. Using the exponential operation on graphs, we can construct various graphs of multi-exponential order with logarithmic diameter. We show that…

Combinatorics · Mathematics 2025-01-28 Toru Hasunuma

Complex numbers define the relationship between entities in many situations. A canonical example would be the off-diagonal terms in a Hamiltonian matrix in quantum physics. Recent years have seen an increasing interest to extend the tools…

Social and Information Networks · Computer Science 2023-07-06 Yu Tian , Renaud Lambiotte

Gaetz, Pechenik, Pfannerer, Striker, and Swanson introduced the concept of hourglass plabic graphs and provided a method for computing web diagrams and invariants corresponding to $4\times n$ Young tableaux, while Elkin, Musiker, and Wright…

Combinatorics · Mathematics 2025-07-25 Wen Ting Zhang , Rui Zhi Tang , Jin Xing Zhao

The collection of data on populations of networks is becoming increasingly common, where each data point can be seen as a realisation of a network-valued random variable. A canonical example is that of brain networks: a typical neuroimaging…

Methodology · Statistics 2021-04-13 Brieuc Lehmann , Simon White

In this thesis I develop a formalism whereby a tensor network may be understood in terms of a unitary braided tensor category, and represented in a particularly efficient manner corresponding to the exploitation of this mathematical…

Strongly Correlated Electrons · Physics 2012-02-13 Robert N. C. Pfeifer

We address here the problem of describing both the total and the elastic proton-proton cross-section, through the four outstanding features of hadron scattering: (i) the optical point; (ii) the forward peak, (iii) the dip and (iv) the…

High Energy Physics - Phenomenology · Physics 2014-04-01 Giulia Pancheri , Daniel A. Fagundes , A. Grau , O. Shekhovtsova , Yogendra N. Srivastava

We evaluate the scattering functions of a gas of spin-polarized, non-interacting fermions confined in a quasi-onedimensional harmonic trap at zero temperature. The main focus is on the inelastic scattering spectrum and on the angular…

Statistical Mechanics · Physics 2009-11-07 Patrizia Vignolo , Anna Minguzzi , M. P. Tosi

We present a method for learning max-weight matching predictors in bipartite graphs. The method consists of performing maximum a posteriori estimation in exponential families with sufficient statistics that encode permutations and data…

Machine Learning · Computer Science 2009-06-05 James Petterson , Tiberio Caetano , Julian McAuley , Jin Yu

An important problem in network analysis is predicting a node attribute using both network covariates, such as graph embedding coordinates or local subgraph counts, and conventional node covariates, such as demographic characteristics.…

Methodology · Statistics 2023-02-24 Robert Lunde , Elizaveta Levina , Ji Zhu

The simplification and reorganization of complex expressions lies at the core of scientific progress, particularly in theoretical high-energy physics. This work explores the application of machine learning to a particular facet of this…

High Energy Physics - Theory · Physics 2025-02-05 Clifford Cheung , Aurélien Dersy , Matthew D. Schwartz

Recent work on the internet, social networks, and the power grid has addressed the resilience of these networks to either random or targeted deletion of network nodes. Such deletions include, for example, the failure of internet routers or…

Statistical Mechanics · Physics 2009-10-31 D. S. Callaway , M. E. J. Newman , S. H. Strogatz , D. J. Watts

We propose a link prediction algorithm that is based on spring-electrical models. The idea to study these models came from the fact that spring-electrical models have been successfully used for networks visualization. A good network…

Social and Information Networks · Computer Science 2019-06-12 Yana Kashinskaya , Egor Samosvat , Akmal Artikov

In this paper, we focus on graph learning from multi-view data of shared entities for spectral clustering. We can explain interactions between the entities in multi-view data using a multi-layer graph with a common vertex set, which…

Machine Learning · Computer Science 2021-03-04 Sravanthi Gurugubelli , Sundeep Prabhakar Chepuri

The advent of non-Hermitian physics has enriched the plethora of topological phases to include phenomena without Hermitian counterparts. Despite being among the most well-studied uniquely non-Hermitian features, the topological properties…

Mesoscale and Nanoscale Physics · Physics 2025-06-05 Marcus Stålhammar , Lukas Rødland

The soft emission factor is a central ingredient in the factorization of generic $n$-particle gauge theory amplitudes with one soft gluon in the external state. We present the complete two-loop soft factor, capturing the leading power…

High Energy Physics - Phenomenology · Physics 2024-05-24 Lance J. Dixon , Enrico Herrmann , Kai Yan , Hua Xing Zhu

Many real world network problems often concern multivariate nodal attributes such as image, textual, and multi-view feature vectors on nodes, rather than simple univariate nodal attributes. The existing graph estimation methods built on…

Machine Learning · Statistics 2013-04-23 Mladen Kolar , Han Liu , Eric P. Xing

Efficient embedding virtual clusters in physical network is a challenging problem. In this paper we consider a scenario where physical network has a structure of a balanced tree. This assumption is justified by many real- world…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-30 Carlo Fuerst , Maciej Pacut , Stefan Schmid