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Suppose a residually finite group $G$ acts cocompactly on a contractible complex with strict fundamental domain $Q$, where the stabilizers are either trivial or have normal $\mathbb{Z}$-subgroups. Let $\partial Q$ be the subcomplex of $Q$…

Group Theory · Mathematics 2024-01-18 Boris Okun , Kevin Schreve

In this paper we indicate one method of construction of linear representations of groups and algebras with translation invariant (except, maybe , finite number) defining relationships. As an illustration of this method, we give one approach…

q-alg · Mathematics 2016-09-08 Vladimir K. Medvedev

We provide two alternative ways to determine the number of (bi-)twisted conjugacy classes in a finite group: one by counting certain irreducible characters and one by counting certain twisted conjugacy classes of other endomorphisms. In…

Group Theory · Mathematics 2026-03-03 Pieter Senden , Sam Tertooy

We show that certain modular induced representations of $\mathrm{GL}_2({\mathbb F}_q)$ can be written as cokernels of operators acting on symmetric power representations of $\mathrm{GL}_2({\mathbb F}_q)$. When the induction is from the…

Representation Theory · Mathematics 2024-11-27 Eknath Ghate , Arindam Jana

In arXiv:2011.03313, the author has constructed a category of abstractly automorphic representations for $\mathrm{GL}(2)$ over a function field $F$. This is a symmetric monoidal Abelian category, constructed with the goal of having the…

Number Theory · Mathematics 2021-02-24 Gal Dor

We initiate the systematic study of modular representations of symmetric groups that arise via the braiding in (symmetric) tensor categories over fields of positive characteristic. We determine what representations appear for certain…

Representation Theory · Mathematics 2026-03-09 Kevin Coulembier

Graph representation learning (a.k.a. network embedding) is a significant topic of network analysis, due to its effectiveness to support various graph inference tasks. In this paper, we study the representation learning with multiple…

Social and Information Networks · Computer Science 2023-05-17 Meng Qin

This paper provides the final ingredient in the development of the deformation theory of pretriangulated dg-categories endowed with a nice t-structure, which was initiated by the authors and is modeled after the previously developed…

Category Theory · Mathematics 2024-11-26 Francesco Genovese , Wendy Lowen , Julie Symons , Michel Van den Bergh

We show that all isomorphism classes of even rank Tambara-Yamagami categories arise as $\mathbb{Z}_2$-twisted representations of conformal nets. As a consequence, we show that their Drinfel'd centers are realized by (generalized) orbifolds…

Quantum Algebra · Mathematics 2018-03-14 Marcel Bischoff

The paper is to classify irreducible integrable modules for the twisted full toroidal Lie algebra with some technical conditions. The twisted full toroidal Lie algebra are extensions of multiloop algebra twisted by sevaral finite order…

Representation Theory · Mathematics 2015-09-10 S. Eswara Rao , Punita Batra

Making use of a unified approach to certain classes of induced representations, we establish here a number of detailed spectral theoretic decomposition results. They apply to specific problems from non-commutative harmonic analysis, ergodic…

Functional Analysis · Mathematics 2015-08-13 Palle Jorgensen , Feng Tian

The symmetry and geometry of input data are considered to be encoded in the internal data representation inside the neural network, but the specific encoding rule has been less investigated. In this study, we present a systematic method to…

Machine Learning · Computer Science 2023-11-14 Sho Sonoda , Hideyuki Ishi , Isao Ishikawa , Masahiro Ikeda

Transformer architectures are typically described in algorithmic and statistical terms, leaving their internal mechanics without a familiar structural language for researchers trained in physical theories. To bridge this gap, we develop a…

Disordered Systems and Neural Networks · Physics 2026-03-18 Po-Hao Chang

We theoretically analyze the Feedback Alignment (FA) algorithm, an efficient alternative to backpropagation for training neural networks. We provide convergence guarantees with rates for deep linear networks for both continuous and discrete…

Machine Learning · Computer Science 2021-10-22 Manuela Girotti , Ioannis Mitliagkas , Gauthier Gidel

We exploit the symmetry concepts developed in the companion review of this article to introduce a stochastic version of link reversal symmetry, which leads to an improved understanding of the reciprocity of directed networks. We apply our…

General Finance · Quantitative Finance 2010-11-04 Franco Ruzzenenti , Diego Garlaschelli , Riccardo Basosi

Representation learning is the first step in automating tasks such as research paper recommendation, classification, and retrieval. Due to the accelerating rate of research publication, together with the recognised benefits of…

Digital Libraries · Computer Science 2023-03-22 Eoghan Cunningham , Derek Greene

A vertex algebra with an action of a group $G$ comes with a notion of $g$-twisted modules, forming a $G$-crossed braided tensor category. For a Lie group $G$, one might instead wish for a notion of $(\mathrm{d}+A)$-twisted modules for any…

Quantum Algebra · Mathematics 2024-12-20 Boris L. Feigin , Simon D. Lentner

This contribution studies a specific deformation of algebras with anti-involution. Starting with the observation that twisting the multiplication of such an algebra by its anti-involution generates a Hom-associative algebra of type II, it…

Rings and Algebras · Mathematics 2023-10-03 Alexis Langlois-Rémillard

In this paper we discuss the inclusion ordering on the filters of a filter algebra, a special type of Metropolis-Rota algeba. Using embeddings into interval algebras we show that the notion of "untwisted" gives rise to a congruence relation…

Rings and Algebras · Mathematics 2009-02-02 Colin Bailey , Joseph Oliveira

Aiming at a comprehensive and concise tutorial survey, recap of variational inference and reinforcement learning with Probabilistic Graphical Models are given with detailed derivations. Reviews and comparisons on recent advances in deep…

Machine Learning · Computer Science 2019-12-10 Xudong Sun , Bernd Bischl