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Multi-graph learning is crucial for extracting meaningful signals from collections of heterogeneous graphs. However, effectively integrating information across graphs with differing topologies, scales, and semantics, often in the absence of…

Machine Learning · Computer Science 2026-02-02 Zahra Moslemi , Ziyi Liang , Norbert Fortin , Babak Shahbaba

Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs (MMKGs), whose entities can be associated with relational triples and related images. Most previous studies treat the graph…

Computation and Language · Computer Science 2024-07-30 Taoyu Su , Xinghua Zhang , Jiawei Sheng , Zhenyu Zhang , Tingwen Liu

We show that soft gluons exchanged between the two colliding protons in multiparton scattering processes can be decoupled, such that their effects are described by the vacuum expectation values of Wilson lines. Our argument relies on…

High Energy Physics - Phenomenology · Physics 2019-05-22 Markus Diehl , Riccardo Nagar

We explicitly show the area law behavior of a circular Wilson loop in confining theories from supergravity. We calculate the correlator of two Wilson loops from supergravity in confining backgrounds. We find that it is dominated by an…

High Energy Physics - Theory · Physics 2010-02-03 J. Sonnenschein , A. Loewy

The Geometry of Interaction purpose is to give a semantic of proofs or programs accounting for their dynamics. The initial presentation, translated as an algebraic weighting of paths in proofnets, led to a better characterization of the…

Logic in Computer Science · Computer Science 2008-04-10 Marc de Falco

Given a semisimple Lie algebra $\mathfrak{g}$, we can represent invariants of tensor products of fundamental representations of the quantum enveloping algebra $U_q(\mathfrak{g})$ using particular directed graphs called webs. In particular…

Quantum Algebra · Mathematics 2018-10-01 Colin Hagemeyer

We propose SWING: Space Walks for Implicit Network Graphs, a new class of algorithms for computations involving Graph Random Features on graphs given by implicit representations (i-graphs), where edge-weights are defined as bi-variate…

Machine Learning · Computer Science 2026-05-19 Alessandro Manenti , Avinava Dubey , Arijit Sehanobish , Cesare Alippi , Krzysztof Choromanski

We study the low-energy limit of Wilson lines (charged impurities) in conformal gauge theories in 2+1 and 3+1 dimensions. As a function of the representation of the Wilson line, certain defect operators can become marginal, leading to…

High Energy Physics - Theory · Physics 2023-04-26 Ofer Aharony , Gabriel Cuomo , Zohar Komargodski , Márk Mezei , Avia Raviv-Moshe

In this paper, we show that Minkowski Functionals (MFs) of weak gravitational lensing (WL) convergence maps contain significant non-Gaussian, cosmology-dependent information. To do this, we use a large suite of cosmological ray-tracing…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-30 Jan M. Kratochvil , Eugene A. Lim , Sheng Wang , Zoltan Haiman , Morgan May , Kevin Huffenberger

Webs are a kind of planar, directed, edge-labeled graph that encode invariant vectors for quantum representations of $\mathfrak{sl}_n$. The theory of webs developed organically for $\mathfrak{sl}_2$, where they are also known as noncrossing…

Representation Theory · Mathematics 2025-10-16 Heather M. Russell , Julianna Tymoczko

This expository article is an introduction to logarithmic Gromov--Witten (GW) theory. We discuss how to study the GW theory of a smooth projective variety via simple normal crossings degenerations. We survey several approaches to…

Algebraic Geometry · Mathematics 2026-03-02 Dhruv Ranganathan

Multimodal data provide complementary information of a natural phenomenon by integrating data from various domains with very different statistical properties. Capturing the intra-modality and cross-modality information of multimodal data is…

Machine Learning · Computer Science 2021-11-29 Maysam Behmanesh , Peyman Adibi , Mohammad Saeed Ehsani , Jocelyn Chanussot

We obtain concise analytic formulae for Wilson loops computed on special n-point polygonal contours through two-loops in weakly coupled N=4 supersymmetric gauge theory. The contours we consider can be embedded into a (1+1)-dimensional…

High Energy Physics - Theory · Physics 2010-11-15 Paul Heslop , Valentin V. Khoze

Gauge invariance in soft-collinear effective theory (SCET) is discussed in regular (covariant) and singular (light-cone) gauges. It is argued that SCET, as it stands, is not capable to define in a gauge invariant way certain…

High Energy Physics - Phenomenology · Physics 2011-01-04 Ahmad Idilbi , Ignazio Scimemi

In a large class of models for Weakly Interacting Massive Particles (WIMPs), the WIMP mass $M$ lies far above the weak scale $m_W$. This work identifies universal Sudakov-type logarithms $\sim \alpha \log^2 (2\,M/m_W)$ that spoil the naive…

High Energy Physics - Phenomenology · Physics 2015-06-23 Martin Bauer , Timothy Cohen , Richard J. Hill , Mikhail P. Solon

When G is a product of orthogonal, unitary and symplectic groups, we show that the Wilson loops generate a dense subalgebra of continuous observables on the configuration space of lattice gauge theory with structure group G.

Mathematical Physics · Physics 2007-05-23 Thierry Levy

Objective: Modelling the associations from high-throughput experimental molecular data has provided unprecedented insights into biological pathways and signalling mechanisms. Graphical models and networks have especially proven to be useful…

Machine Learning · Statistics 2013-04-24 Marco Scutari , Radhakrishnan Nagarajan

Modular graph functions (MGFs) are $\mathrm{SL}(2,\mathbb{Z})$-invariant functions on the Poincar\'e upper half-plane associated with Feynman graphs of a conformal scalar field on a torus. The low-energy expansion of genus-one superstring…

High Energy Physics - Theory · Physics 2022-02-23 Eric D'Hoker , Nicholas Geiser

Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressive power of graph neural networks (GNN). It was shown that the popular message passing GNN cannot distinguish between graphs that are…

Machine Learning · Computer Science 2020-06-11 Haggai Maron , Heli Ben-Hamu , Hadar Serviansky , Yaron Lipman

The theory of Wilson loops for gauge theories with unitary gauge groups is formulated in the language of symmetric functions. The main objects in this theory are two generating functions, which are related to each other by the involution…

High Energy Physics - Theory · Physics 2019-11-20 Wolfgang Mück