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Markov categories are a novel framework to describe and treat problems in probability and information theory. In this work we combine the categorical formalism with the traditional quantitative notions of entropy, mutual information, and…

Information Theory · Computer Science 2024-04-15 Paolo Perrone

This contribution proposes a new approach towards developing a class of probabilistic methods for classifying attributed graphs. The key concept is random attributed graph, which is defined as an attributed graph whose nodes and edges are…

Computer Vision and Pattern Recognition · Computer Science 2011-09-23 S. Deepak Srinivasan , Klaus Obermayer

This paper addresses fundamental issues on the nature of the concepts and structures of fuzzy logic, focusing, in particular, on the conceptual and functional differences that exist between probabilistic and possibilistic approaches. A…

Artificial Intelligence · Computer Science 2013-04-05 Enrique H. Ruspini

Formal patterns are formally specified solutions to frequently occurring distributed system problems that are generic, executable, and come with strong qualitative and/or quantitative formal guarantees. A formal pattern is a generic system…

Cryptography and Security · Computer Science 2026-03-23 Víctor García , Santaigo Escobar , Catherine Meadows , Jose Meseguer

Tight bounds on the block entropy of patterns of sequences generated by independent and identically distributed (i.i.d.) sources are derived. A pattern of a sequence is a sequence of integer indices with each index representing the order of…

Information Theory · Computer Science 2007-11-14 Gil I. Shamir

Pseudoentropy characterizations provide a quantitatively precise demonstration of the close relationship between computational hardness and computational randomness. We prove a unified pseudoentropy characterization that generalizes and…

Computational Complexity · Computer Science 2025-09-05 Lunjia Hu , Salil Vadhan

Session types describe the structure of communications implemented by channels. In particular, they prescribe the sequence of communications, whether they are input or output actions, and the type of value exchanged. Crucial to any language…

Logic in Computer Science · Computer Science 2023-06-22 Dimitris Mostrous , Vasco T. Vasconcelos

A series of recent papers by Bergfalk, Lupini and Panagiotopoulus developed the foundations of a field known as `definable algebraic topology,' in which classical cohomological invariants are enriched by viewing them as groups with a Polish…

Logic · Mathematics 2025-07-21 Nicholas Meadows

Comparing networks is essential for a number of downstream tasks, from clustering to anomaly detection. Despite higher-order interactions being critical for understanding the dynamics of complex systems, traditional approaches for network…

Physics and Society · Physics 2025-11-03 Helcio Felippe , Alec Kirkley , Federico Battiston

It has been shown in a recent publication that words in human-produced English language tend to have an information content close to the conditional entropy. In this paper, we show that the same is true for events in human-produced…

Sound · Computer Science 2022-11-24 Mathias Rose Bjare , Stefan Lattner

This work represents an in-depth study of the structural behavior of the Collatz sequences. We consider a finite arithmetic progression with a common difference is 2 and the number of terms in the sequence is equal to 2^n . After, we…

General Mathematics · Mathematics 2021-04-26 Raouf Rajab

A strongly polynomial sequence of graphs $(G_n)$ is a sequence $(G_n)_{n\in\mathbb{N}}$ of finite graphs such that, for every graph $F$, the number of homomorphisms from $F$ to $G_n$ is a fixed polynomial function of $n$ (depending on $F$).…

Combinatorics · Mathematics 2016-08-09 Andrew Goodall , Jaroslav Nesetril , Patrice Ossona de Mendez

Compositional generalization is a fundamental trait in humans, allowing us to effortlessly combine known phrases to form novel sentences. Recent works have claimed that standard seq-to-seq models severely lack the ability to compositionally…

Computation and Language · Computer Science 2022-03-16 Arkil Patel , Satwik Bhattamishra , Phil Blunsom , Navin Goyal

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely…

Physics and Society · Physics 2012-06-11 Stefano Cardanobile , Volker Pernice , Moritz Deger , Stefan Rotter

Network coding theory studies the transmission of information in networks whose vertices may perform nontrivial encoding and decoding operations on data as it passes through the network. The main approach to deciding the feasibility of…

Information Theory · Computer Science 2010-01-12 Anna Blasiak , Robert Kleinberg

Models of complex networks are generally defined as graph stochastic processes in which edges and vertices are added or deleted over time to simulate the evolution of networks. Here, we define a unifying framework - probabilistic inductive…

Dynamical Systems · Mathematics 2010-11-10 Nataša Kejžar , Zoran Nikoloski , Vladimir Batagelj

The law of large numbers is one of the most fundamental results in Probability Theory. In the case of independent sequences, there are some known characterizations; for instance, in the independent and identically distributed setting it is…

Probability · Mathematics 2020-08-04 Luísa Borsato , Eduardo Horta , Rafael Rigão Souza

A generic uniformly distributed sequence $(x_n)_{n \in \mathbb{N}}$ in $[0,1)$ possesses Poissonian pair correlations (PPC). Vice versa, it has been proven that a sequence with PPC is uniformly distributed. Grepstad and Larcher gave an…

Number Theory · Mathematics 2022-06-30 Christian Weiß

It is proved that the Continuum Hypothesis implies that any sequence of rapid P-points of length $<{\mathfrak c}^{+}$ which is increasing with respect to the Rudin-Keisler ordering is bounded above by a rapid P-point. This is an improvement…

Logic · Mathematics 2019-02-14 Dilip Raghavan , Jonathan L. Verner

Large graphs are sometimes studied through their degree sequences (power law or regular graphs). We study graphs that are uniformly chosen with a given degree sequence. Under mild conditions, it is shown that sequences of such graphs have…

Probability · Mathematics 2011-08-31 Sourav Chatterjee , Persi Diaconis , Allan Sly