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The G-Wishart distribution is an essential component for the Bayesian analysis of Gaussian graphical models as the conjugate prior for the precision matrix. Evaluating the marginal likelihood of such models usually requires computing…

Methodology · Statistics 2025-04-11 Ching Wong , Giusi Moffa , Jack Kuipers

There exists a well established differential topological theory of singularities of ordinary differential equations. It has mainly studied scalar equations of low order. We propose an extension of the key concepts to arbitrary systems of…

Commutative Algebra · Mathematics 2021-03-12 Markus Lange-Hegermann , Daniel Robertz , Werner M. Seiler , Matthias Seiss

Graph transformation that predicts graph transition from one mode to another is an important and common problem. Despite much progress in developing advanced graph transformation techniques in recent years, the fundamental assumption…

Machine Learning · Computer Science 2023-05-25 Shiyu Wang , Guangji Bai , Qingyang Zhu , Zhaohui Qin , Liang Zhao

We prove a complexity dichotomy theorem for Holant problems over an arbitrary set of complex-valued symmetric constraint functions F on Boolean variables. This extends and unifies all previous dichotomies for Holant problems on symmetric…

Computational Complexity · Computer Science 2018-01-11 Jin-Yi Cai , Heng Guo , Tyson Williams

Despite their popularity, to date, the application of normalizing flows on categorical data stays limited. The current practice of using dequantization to map discrete data to a continuous space is inapplicable as categorical data has no…

Machine Learning · Computer Science 2021-01-22 Phillip Lippe , Efstratios Gavves

In this work we develop a theory of hierarchical clustering for graphs. Our modeling assumption is that graphs are sampled from a graphon, which is a powerful and general model for generating graphs and analyzing large networks. Graphons…

Machine Learning · Statistics 2017-05-24 Justin Eldridge , Mikhail Belkin , Yusu Wang

In this paper, we revisit a well-known distributed projected subgradient algorithm which aims to minimize a sum of cost functions with a common set constraint. In contrast to most of existing results, weight matrices of the time-varying…

Optimization and Control · Mathematics 2021-04-29 Weijian Li , Zihan Chen , Youcheng Lou , Yiguang Hong

Graph neural networks (GNNs) have emerged as a powerful tool for modeling graph-structured data. However, existing GNNs often struggle with heterophilic graphs, where connected nodes tend to have dissimilar features or labels. While…

Machine Learning · Computer Science 2025-09-17 Ruizhong Qiu , Ting-Wei Li , Gaotang Li , Hanghang Tong

In this paper, we present a modern version of Gordan's algorithm on binary forms. Symbolic method is reinterpreted in terms of $\mathsf{SL}_2(\mathbb{C})$--equivariant homomorphisms defined upon Cayley operator and polarization operator. A…

Representation Theory · Mathematics 2015-06-22 Marc Olive

Given an abelian category and a stability condition satisfying appropriate conditions, we define generalized $K$-theoretic invariants and prove that they satisfy wall-crossing formulas. For this, we introduce a new associative algebra…

Algebraic Geometry · Mathematics 2026-04-08 Ivan Karpov , Miguel Moreira

Signed networks, characterized by edges labeled as either positive or negative, offer nuanced insights into interaction dynamics beyond the capabilities of unsigned graphs. Central to this is the task of identifying the maximum balanced…

Social and Information Networks · Computer Science 2024-06-18 Jingbang Chen , Qiuyang Mang , Hangrui Zhou , Richard Peng , Yu Gao , Chenhao Ma

For any given graph $H$, one may define a natural corresponding functional $\|.\|_H$ for real-valued functions by using homomorphism density. One may also extend this to complex-valued functions, once $H$ is paired with a $2$-edge-colouring…

Combinatorics · Mathematics 2022-09-07 Joonkyung Lee , Alexander Sidorenko

This paper develops an adaptive version of Mallat's scattering transform for signals on graphs. The main results are norm bounds for the layers of the transform, obtained from a version of a Beurling-Deny inequality that permits to remove…

Statistics Theory · Mathematics 2022-08-29 Bernhard G. Bodmann , Iris Emilsdottir

Some sorts of generalized morphisms are defined from very basic mathematical objects such as sets, functions, and partial functions. A wide range of mathematical notions such as continuous functions between topological spaces, ring…

Rings and Algebras · Mathematics 2024-07-24 Gang Hu

Gauging is a general procedure for mapping a quantum many-body system with a global symmetry to one with a local gauge symmetry. We consider a generalized gauging map that does not enforce gauge symmetry at all lattice sites, and show that…

Quantum Physics · Physics 2024-03-15 Kfir Dolev , Vladimir Calvera , Sam Cree , Dominic J. Williamson

Normalized-cut graph partitioning aims to divide the set of nodes in a graph into $k$ disjoint clusters to minimize the fraction of the total edges between any cluster and all other clusters. In this paper, we consider a fair variant of the…

Machine Learning · Computer Science 2023-10-10 Jia Li , Yanhao Wang , Arpit Merchant

'Holographic' relations between theories have become an important theme in quantum gravity research. These relations entail that a theory without gravity is equivalent to a gravitational theory with an extra spatial dimension. The idea of…

High Energy Physics - Theory · Physics 2015-09-11 Dennis Dieks , Jeroen van Dongen , Sebastian de Haro

In combinatorial commutative algebra and algebraic statistics many toric ideals are constructed from graphs. Keeping the categorical structure of graphs in mind we give previous results a more functorial context and generalize them by…

Commutative Algebra · Mathematics 2011-10-04 Alexander Engstrom , Patrik Noren

Open-world semi-supervised learning aims at inferring both known and novel classes in unlabeled data, by harnessing prior knowledge from a labeled set with known classes. Despite its importance, there is a lack of theoretical foundations…

Machine Learning · Computer Science 2023-11-08 Yiyou Sun , Zhenmei Shi , Yixuan Li

I present a method of quantization using cohomology groups extended via coefficient groups of different types. This is possible according to the Universal Coefficient Theorem (UCT). I also show that by using this method new features of…

General Relativity and Quantum Cosmology · Physics 2015-02-18 Andrei T. Patrascu
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