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Graph embeddings have become a key and widely used technique within the field of graph mining, proving to be successful across a broad range of domains including social, citation, transportation and biological. Graph embedding techniques…

Machine Learning · Computer Science 2018-06-21 Stephen Bonner , Ibad Kureshi , John Brennan , Georgios Theodoropoulos , Andrew Stephen McGough , Boguslaw Obara

Due to the advent of the expressions of data other than tabular formats, the topological compositions which make samples interrelated came into prominence. Analogically, those networks can be interpreted as social connections, dataflow…

Social and Information Networks · Computer Science 2023-01-27 Hacı İsmail Aslan , Chang Choi , Hoon Ko

This work deals with relations between a bounded cohomological invariant and the geometry of Hermitian symmetric spaces of noncompact type. The invariant, obtained from the K\"ahler class, is used to define and characterize a special class…

Differential Geometry · Mathematics 2007-05-23 Anna Wienhard

We investigate the relationship between the geometry of token embeddings and their role in the next token prediction within transformer models. An important aspect of this connection uses the notion of empirical measure, which encodes the…

Computation and Language · Computer Science 2025-01-22 Karthik Viswanathan , Yuri Gardinazzi , Giada Panerai , Alberto Cazzaniga , Matteo Biagetti

Classification of large and dense networks based on topology is very difficult due to the computational challenges of extracting meaningful topological features from real-world networks. In this paper we present a computationally tractable…

Machine Learning · Computer Science 2022-02-04 Tananun Songdechakraiwut , Bryan M. Krause , Matthew I. Banks , Kirill V. Nourski , Barry D. Van Veen

Two neural networks which are trained on their mutual output bits show a novel phenomenon: The networks synchronize to a state with identical time dependent weights. It is shown how synchronization by mutual learning can be applied to…

Disordered Systems and Neural Networks · Physics 2007-05-23 Wolfgang Kinzel , Ido Kanter

For a (semi-)model category M, we define a notion of a ''homotopy'' Grothendieck topology on M, as well as its associated model category of stacks. We use this to define a notion of geometric stack over a symmetric monoidal base model…

Algebraic Geometry · Mathematics 2007-05-23 Bertrand Toen , Gabriele Vezzosi

We use monoidal category methods to study the noncommutative geometry of nonassociative algebras obtained by a Drinfeld-type cochain twist. These are the so-called quasialgebras and include the octonions as braided-commutative but…

Quantum Algebra · Mathematics 2015-06-26 S. E. Akrami , S. Majid

We give a construction of cyclic cocycles on convolution algebras twisted by gerbes over discrete translation groupoids. For proper \'etale groupoids, Tu and Xu provide a map between the periodic cyclic cohomology of a gerbe-twisted…

Quantum Algebra · Mathematics 2015-05-27 Eitan Angel

We model problems as presheaves that assign sets of certificates to input instances, and we show how to use presheaf \v{C}ech cohomology to capture the precise ways in which local solutions fail to patch into global ones. Applied to…

Commutative Algebra · Mathematics 2025-11-03 Anny Beatriz Azevedo , Benjamin Merlin Bumpus , Matteo Capucci , James Fairbanks , Daniel Rosiak

We define the notion of a twisted topological graph algebra associated to a topological graph and a $1$-cocycle on its edge set. We prove a stronger version of a Vasselli's result. We expand Katsura's results to study twisted topological…

Operator Algebras · Mathematics 2019-02-20 Hui Li

We will consider P-graph complexes, where P is a cyclic operad. P-graph complexes are natural generalizations of Kontsevich's graph complexes -- for P = the operad for associative algebras it is the complex of ribbon graphs, for P = the…

Quantum Algebra · Mathematics 2016-09-07 Martin Markl

Polymer networks invariably possess topological inhomogeneities in the form of loops and dangling ends. The macroscopic properties of such materials are directly dependent on the local cyclic topology around nodes and chains. Here, a new…

Materials Science · Physics 2024-06-27 Devosmita Sen , Bradley D. Olsen

Homomorphic encryption is a powerful cryptographic tool that enables secure computations on the private data. It evaluates any function for any operation securely on the encrypted data without knowing its corresponding plaintext. For…

Cryptography and Security · Computer Science 2025-09-18 Giovanni Giuseppe Grimaldi

This tutorial covers a few recent papers in the field of network embedding. Network embedding is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space. To be useful, a good embedding…

Social and Information Networks · Computer Science 2019-10-17 Boaz Shmueli

In this paper we generalize the concept of random networks to describe networks with non trivial features by a statistical mechanics approach. This framework is able to describe ensembles of undirected, directed as well as weighted…

Disordered Systems and Neural Networks · Physics 2009-11-13 Ginestra Bianconi

General cryptographic schemes are presented where keys can be one-time or ephemeral. Processes for key exchange are derived. Public key cryptographic schemes based on the new systems are easily established. Authentication and signature…

Cryptography and Security · Computer Science 2020-04-13 Ted Hurley

We provide a new construction of the topological cyclic homology $TC(C)$ of any spectrally-enriched $\infty$-category $C$, which affords a precise algebro-geometric interpretation of the cyclotomic trace map $K(X) \to TC(X)$ from algebraic…

Algebraic Topology · Mathematics 2017-10-18 David Ayala , Aaron Mazel-Gee , Nick Rozenblyum

Recent development of network structure analysis shows that it plays an important role in characterizing complex system of many branches of sciences. Different from previous network centrality measures, this paper proposes the notion of…

Information Retrieval · Computer Science 2009-02-12 Hai Zhuge , Junsheng Zhang

We study a class models of correlated random networks in which vertices are characterized by \textit{hidden variables} controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological…

Disordered Systems and Neural Networks · Physics 2009-11-10 Marian Boguna , Romualdo Pastor-Satorras