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Multi-domain graph pre-training integrates knowledge from diverse domains to enhance performance in the target domains, which is crucial for building graph foundation models. Despite initial success, existing solutions often fall short of…

Machine Learning · Computer Science 2026-03-03 Li Sun , Zhenhao Huang , Silei Chen , Lanxu Yang , Junda Ye , Sen Su , Philip S. Yu

Graph signals are widely used to describe vertex attributes or features in graph-structured data, with applications spanning the internet, social media, transportation, sensor networks, and biomedicine. Graph signal processing (GSP) has…

Signal Processing · Electrical Eng. & Systems 2025-05-22 Yu Zhang , Linyu Peng , Bing-Zhao Li

It is shown that the heat kernel operator for the Laplace operator on any covariantly constant curved background, i.e. in symmetric spaces, may be presented in form of an averaging over the Lie group of isometries with some nontrivial…

High Energy Physics - Theory · Physics 2009-10-28 Ivan G. Avramidi

These notes contain a survey of some aspects of the theory of graded differential algebras and of noncommutative differential calculi as well as of some applications connected with physics. They also give a description of several new…

Quantum Algebra · Mathematics 2007-05-23 Michel Dubois-Violette

High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from high variance and performs poorly in general. We explore…

Machine Learning · Computer Science 2012-06-26 Joshua Dillon , Yi Mao , Guy Lebanon , Jian Zhang

We introduce and study Laplacians on a finite metric graph endowed with generalized densities, that is, measures of finite mass. One important motivation is that this setting provides a common framework for several interesting classes of…

Spectral Theory · Mathematics 2025-12-24 Kiyan Naderi , Noema Nicolussi

This note surveys some classical results and recent developments on the interplay between lower curvature bounds and the isoperimetric problem. It is based on mini-courses given at the European Doctorate School of Differential Geometry…

Differential Geometry · Mathematics 2025-09-24 Gioacchino Antonelli

Kernels are a fundamental technical primitive in machine learning. In recent years, kernel-based methods such as Gaussian processes are becoming increasingly important in applications where quantifying uncertainty is of key interest. In…

We examine a Geometric Deep Learning model as a thermodynamic system treating the weights as non-quantum and non-relativistic particles. We employ the notion of temperature previously defined in [7] and study it in the various layers for…

Machine Learning · Computer Science 2023-09-06 M. Lapenna , F. Faglioni , F. Zanchetta , R. Fioresi

This is lecture notes for a course given at the PCMI Summer School "Quantum Field Theory and Manifold Invariants" (July 1 -- July 5, 2019). I describe basics of gauge-theoretic approach to construction of invariants of manifolds. The main…

Differential Geometry · Mathematics 2019-10-24 Andriy Haydys

We will discuss what it means for a general heat kernel on a metric measure space to be local. We show that the Wiener measure associated to Brownian motion is local. Next we show that locality of the Wiener measure plus a suitable decay…

Metric Geometry · Mathematics 2017-11-08 Olaf Post , Ralf Rückriemen

We consider a quantum graph where the operator contains a potential. We show that this operator admits a heat kernel. Under some assumptions on the potential, this heat kernel admits an asymptotic expansion at t=0 with coefficients that…

Analysis of PDEs · Mathematics 2012-12-13 Ralf Rueckriemen

Lecture notes from the course given by Professor Julia Kempe at the summer school "Statistical physics of Machine Learning" in Les Houches. The notes discuss the so-called NTK approach to problems in machine learning, which consists of…

Machine Learning · Computer Science 2023-07-07 Francesco Cagnetta , Deborah Oliveira , Mahalakshmi Sabanayagam , Nikolaos Tsilivis , Julia Kempe

In contrast to the usual quantum systems which have at most a finite number of open spectral gaps if they are periodic in more than one direction, periodic quantum graphs may have gaps arbitrarily high in the spectrum. This property of…

Quantum Physics · Physics 2020-05-26 Pavel Exner , Ondřej Turek

Quantum geometry on a discrete set means a directed graph with a weight associated to each arrow defining the quantum metric. However, these `lattice spacing' weights do not have to be independent of the direction of the arrow. We use this…

Mathematical Physics · Physics 2020-02-28 Shahn Majid

The purpose of this paper is to develop a "calculus" on graphs that allows graph theory to have new connections to analysis. For example, our framework gives rise to many new partial differential equations on graphs, most notably a new…

Discrete Mathematics · Computer Science 2007-05-23 Joel Friedman , Jean-Pierre Tillich

This is the introduction and bibliography for lecture notes of a course given at the Summer School on Noncommutative Geometry and Applications, sponsored by the European Mathematical Society, at Monsaraz and Lisboa, Portugal, September…

Mathematical Physics · Physics 2008-11-06 Joseph C. Varilly

The fundamental role of on-shell diagrams in quantum field theory has been recently recognized. On-shell diagrams, or equivalently bipartite graphs, provide a natural bridge connecting gauge theory to powerful mathematical structures such…

High Energy Physics - Theory · Physics 2015-06-17 Sebastian Franco , Daniele Galloni , Alberto Mariotti

Quantum graphs are commonly used as models of complex quantum systems, for example molecules, networks of wires, and states of condensed matter. We consider quantum statistics for indistinguishable spinless particles on a graph,…

Mathematical Physics · Physics 2011-01-11 JM Harrison , JP Keating , JM Robbins

We study the spectral aspects of the graph limit theory. We give a description of graphon convergence in terms of converegnce of eigenvalues and eigenspaces. Along these lines we prove a spectral version of the strong regularity lemma.…

Combinatorics · Mathematics 2010-03-31 Balazs Szegedy
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