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Topologically ordered systems are characterized by topological invariants that are often calculated from the momentum space integration of a certain function that represents the curvature of the many-body state. The curvature function may…

Mesoscale and Nanoscale Physics · Physics 2016-01-21 Wei Chen

We consider phase transitions in the standard model (SM) without the Higgs mass term, which is coupled through a Higgs portal term to an SM singlet, classically scale-invariant gauge sector with SM singlet scalar fields. At lower energies…

High Energy Physics - Phenomenology · Physics 2015-09-08 Jisuke Kubo , Masatoshi Yamada

A signed graph is a graph where the edges are assigned labels of either "$+$" or "$-$". The sign of a cycle in the graph is the product of the signs of its edges. We equip each signed complete graph with a vector whose entries are the…

Combinatorics · Mathematics 2017-07-03 Alex Schaefer

A gain graph over a group $G$, also referred to as $G$-gain graph, is a graph where an element of a group $G$, called gain, is assigned to each oriented edge, in such a way that the inverse element is associated with the opposite…

Combinatorics · Mathematics 2023-04-10 Aida Abiad , Francesco Belardo , Antonina P. Khramova

It is well known that a graph $G$ has a symmetric spectrum if and only if it is bipartite, a signed graph $\Gamma=(G,\sigma)$ has a symmetric spectrum if $G$ is bipartite. However, there exists a spectrally symmetric signed graph…

Combinatorics · Mathematics 2025-05-02 Deqiong Li , Qiongxiang Huang

Scene Graph Generation (SGG) suffers from a long-tailed distribution, where a few predicate classes dominate while many others are underrepresented, leading to biased models that underperform on rare relations. Unbiased-SGG methods address…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Runfeng Qu , Ole Hall , Pia K Bideau , Julie Ouerfelli-Ethier , Martin Rolfs , Klaus Obermayer , Olaf Hellwich

Accurate multivariate time series forecasting hinges on inter-series correlations, which often evolve in complex ways across different temporal scales. Existing methods are limited in modeling these multi-scale dependencies and struggle to…

Machine Learning · Computer Science 2026-01-27 Shaoxun Wang , Xingjun Zhang , Qianyang Li , Jiawei Cao , Zhendong Tan

Bayesian networks are a widely-used class of probabilistic graphical models capable of representing symmetric conditional independence between variables of interest using the topology of the underlying graph. For categorical variables, they…

Machine Learning · Statistics 2022-10-07 Gherardo Varando , Federico Carli , Manuele Leonelli

There is a pressing need for a description of complex systems that includes considerations of the underlying network of interactions, for a diverse range of biological, technological and other networks. In this work relationships between…

Disordered Systems and Neural Networks · Physics 2007-05-23 Samantha Jenkins , Steven R. Kirk

Signed graphs model complex relationships through positive and negative edges, with widespread real-world applications. Given the sensitive nature of such data, selective removal mechanisms have become essential for privacy protection.…

Machine Learning · Computer Science 2025-11-19 Junpeng Zhao , Lin Li , Kaixi Hu , Kaize Shi , Jingling Yuan

An oriented hypergraph is an oriented incidence structure that extends the concept of a signed graph. We introduce hypergraphic structures and techniques central to the extension of the circuit classification of signed graphs to oriented…

Combinatorics · Mathematics 2016-01-21 Lucas J. Rusnak

Graph based representation has been widely used in modelling spatio-temporal relationships in video understanding. Although effective, existing graph-based approaches focus on capturing the human-object relationships while ignoring…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Chinthani Sugandhika , Chen Li , Deepu Rajan , Basura Fernando

Graph or network data is ubiquitous in the real world, including social networks, information networks, traffic networks, biological networks and various technical networks. The non-Euclidean nature of graph data poses the challenge for…

Social and Information Networks · Computer Science 2019-09-06 Junjie Huang , Huawei Shen , Liang Hou , Xueqi Cheng

A signed graph $\Sigma$ is a pair $(G,\sigma)$, where $G=(V,E)$ is the underlying graph in which each edge is assigned $+1$ or $-1$ by the signature function $\sigma:E\rightarrow\{-1,+1\}$. In this paper, we extend the extensively applied…

Combinatorics · Mathematics 2021-06-24 Shahul Hameed K , Remna K P , Divya T2 , Biju K , Rajeevan P , Santhosh G O2 , Ramakrishnan K O

Cycle switching is a particular form of transformation applied to isomorphism classes of a Steiner triple system of a given order $v$ (an $STS(v)$), yielding another $STS(v)$. This relationship may be represented by an undirected graph. An…

Combinatorics · Mathematics 2024-05-14 Grahame Erskine , Terry S. Griggs

The phase space for a system of $n$ qubits is a discrete grid of $2^{n} \times 2^{n}$ points, whose axes are labeled in terms of the elements of the finite field $\Gal{2^n}$ to endow it with proper geometrical properties. We analyze the…

Quantum Physics · Physics 2012-05-10 A. B. Klimov , C. Munoz , L. L. Sanchez-Soto

Hilbert-space fragmentation provides a mechanism for ergodicity breaking in quantum many-body systems even in the absence of disorder, leading to dynamically disconnected sectors and strong memory of initial conditions. However, identifying…

Strongly Correlated Electrons · Physics 2026-05-19 A. Rutkowski , M. Mierzejewski , J. Herbrych

Given a family of systems, identifying stabilizing switching signals in terms of infinite walks constructed by concatenating cycles on the underlying directed graph of a switched system that satisfy certain conditions, is a well-known…

Systems and Control · Computer Science 2020-05-18 Atreyee Kundu

Semi-supervised learning (SSL) has tremendous value in practice due to its ability to utilize both labeled data and unlabelled data. An important class of SSL methods is to naturally represent data as graphs such that the label information…

Machine Learning · Computer Science 2021-03-01 Zixing Song , Xiangli Yang , Zenglin Xu , Irwin King

We develop a formalism to address statistical pattern recognition of graph valued data. Of particular interest is the case of all graphs having the same number of uniquely labeled vertices. When the vertex labels are latent, such graphs are…

Quantitative Methods · Quantitative Biology 2012-10-17 Joshua T. Vogelstein , Carey E. Priebe