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We consider state-based systems modelled as coalgebras whose type incorporates branching, and show that by suitably adapting the definition of coalgebraic bisimulation, one obtains a general and uniform account of the linear-time behaviour…

Logic in Computer Science · Computer Science 2013-09-05 Corina Cirstea

We consider the behavior of a collective variable in a complex system formed by a finite number of interacting subunits. Each of them is characterized by a degree of freedom with an intrinsic nonlinear bistable stochastic dynamics. The lack…

Statistical Mechanics · Physics 2017-03-16 M. Morillo , J. M. Casado

Wegner describes coordination as constrained interaction. We take this approach literally and define a coordination model based on interaction constraints and partial, iterative and interactive constraint satisfaction. Our model captures…

Logic in Computer Science · Computer Science 2009-12-01 Dave Clarke , José Proença

In this work clustering schemes for uncertain and structured data are considered relying on the notion of Wasserstein barycenters, accompanied by appropriate clustering indices based on the intrinsic geometry of the Wasserstein space where…

Differences in opinion can be seen as distances between individuals, and such differences do not always vanish over time. In this paper, we propose a modeling framework that captures the formation of opinion clusters, based on extensions of…

Dynamical Systems · Mathematics 2025-06-09 Christian Kuehn , Jaeyoung Yoon

We propose new summary measures of diagnostic test accuracy which can be used as companions to existing diagnostic accuracy measures. Conceptually, our summary measures are tantamount to the so-called Hellinger affinity and we show that…

Methodology · Statistics 2017-12-29 Miguel de Carvalho , Bradley J. Barney , Garritt L. Page

Conformational transitions are ubiquitous in biomolecular systems, have significant functional roles and are subject to evolutionary pressures. Here we provide a first theoretical framework for topological transition, i.e. conformational…

Disordered Systems and Neural Networks · Physics 2015-09-02 Alireza Mashaghi , Abolfazl Ramezanpour

Before we attempt to learn a function between two (sets of) observables of a physical process, we must first decide what the inputs and what the outputs of the desired function are going to be. Here we demonstrate two distinct, data-driven…

Optimal transport provides a powerful mathematical framework with applications spanning numerous fields. A cornerstone within this domain is the $p$-Wasserstein distance, which serves to quantify the cost of transporting one probability…

Quantum Physics · Physics 2025-03-13 Emily Beatty , Daniel Stilck França

Word embeddings are high dimensional vector representations of words that capture their semantic similarity in the vector space. There exist several algorithms for learning such embeddings both for a single language as well as for several…

Computation and Language · Computer Science 2019-11-12 Georgios Balikas , Ioannis Partalas

Optimal transport is widely used in pure and applied mathematics to find probabilistic solutions to hard combinatorial matching problems. We extend the Wasserstein metric and other elements of optimal transport from the matching of sets to…

Optimization and Control · Mathematics 2019-07-16 Evan Patterson

We establish quantitative comparisons between classical distances for probability distributions belonging to the class of convex probability measures. Distances include total variation distance, Wasserstein distance, Kullback-Leibler…

Probability · Mathematics 2021-12-17 Arnaud Marsiglietti , Puja Pandey

The analysis and control of stochastic dynamical systems rely on probabilistic models such as (continuous-space) Markov decision processes, but large or continuous state spaces make exact analysis intractable and call for principled…

Logic in Computer Science · Computer Science 2026-03-13 Nivar Anwer , Ezequiel López-Rubio , David Elizondo , Rafael M. Luque-Baena

Disentangling polysemantic neurons is at the core of many current approaches to interpretability of large language models. Here we attempt to study how disentanglement can be used to understand performance, particularly under weight…

Machine Learning · Computer Science 2025-02-27 Shashata Sawmya , Linghao Kong , Ilia Markov , Dan Alistarh , Nir Shavit

Motivated by problems in data clustering, we establish general conditions under which families of nonparametric mixture models are identifiable, by introducing a novel framework involving clustering overfitted \emph{parametric} (i.e.…

Statistics Theory · Mathematics 2020-02-19 Bryon Aragam , Chen Dan , Eric P. Xing , Pradeep Ravikumar

We establish the first mathematically rigorous link between Bayesian, variational Bayesian, and ensemble methods. A key step towards this it to reformulate the non-convex optimisation problem typically encountered in deep learning as a…

Machine Learning · Statistics 2023-10-24 Veit David Wild , Sahra Ghalebikesabi , Dino Sejdinovic , Jeremias Knoblauch

In this paper we propose an algorithm for aligning three-dimensional objects when represented as density maps, motivated by applications in cryogenic electron microscopy. The algorithm is based on minimizing the 1-Wasserstein distance…

Image and Video Processing · Electrical Eng. & Systems 2024-03-13 Amit Singer , Ruiyi Yang

The loss of criticality in the form of weak first-order transitions or the end of the conformal window in gauge theories can be described as the merging of two fixed points that move to complex values of the couplings. When the complex…

High Energy Physics - Theory · Physics 2020-05-06 Anton F. Faedo , Carlos Hoyos , David Mateos , Javier G. Subils

We revisit the phenomenon of syntactic complexity convergence in conversational interaction, originally found for English dialogue, which has theoretical implication for dialogical concepts such as mutual understanding. We use a modified…

Computation and Language · Computer Science 2024-08-23 Yu Wang , Hendrik Buschmeier

Four-dimensional gauge theories with matter can have regions in parameter space, often dubbed conformal windows, where they flow in the infrared to non-trivial conformal field theories. It has been conjectured that conformality can be lost…

High Energy Physics - Theory · Physics 2021-08-25 Francesco Benini , Cristoforo Iossa , Marco Serone