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Characteristic formulae give a complete logical description of the behaviour of processes modulo some chosen notion of behavioural semantics. They allow one to reduce equivalence or preorder checking to model checking, and are exactly the…

Logic in Computer Science · Computer Science 2026-03-27 Luca Aceto , Antonis Achilleos , Aggeliki Chalki , Anna Ingolfsdottir

Time series classification is an important task in its own right, and it is often a precursor to further downstream analytics. To date, virtually all works in the literature have used either shape-based classification using a distance…

Machine Learning · Computer Science 2019-12-23 Sara Alaee , Alireza Abdoli , Christian Shelton , Amy C. Murillo , Alec C. Gerry , Eamonn Keogh

I introduce a general, Bayesian method for modelling univariate time series data assumed to be drawn from a continuous, stochastic process. The method accommodates arbitrary temporal sampling, and takes into account measurement…

Instrumentation and Methods for Astrophysics · Physics 2012-10-24 C. A. L. Bailer-Jones

The sequence of moments of a vector-valued random variable can characterize its law. We study the analogous problem for path-valued random variables, that is stochastic processes, by using so-called robust signature moments. This allows us…

Statistics Theory · Mathematics 2022-09-16 Ilya Chevyrev , Harald Oberhauser

Cities can be seen as the epitome of complex systems. They arise from a set of interactions and components so diverse that is almost impossible to describe them exhaustively. Amid this diversity, we chose an object which orchestrates the…

Physics and Society · Physics 2015-12-07 Claire Lagesse

In this work we extend the Emerson and Kahlon's cutoff theorems for process skeletons with conjunctive guards to Parameterized Networks of Timed Automata, i.e. systems obtained by an \emph{apriori} unknown number of Timed Automata…

Logic in Computer Science · Computer Science 2016-05-20 Luca Spalazzi , Francesco Spegni

Visual localization is a useful alternative to standard localization techniques. It works by utilizing cameras. In a typical scenario, features are extracted from captured images and compared with geo-referenced databases. Location…

Computer Vision and Pattern Recognition · Computer Science 2020-06-28 Li Weng , Valerie Gouet-Brunet , Bahman Soheilian

Motion is a fundamental cue for scene analysis and human activity understan- ding in videos. It can be encoded in trajectories for tracking objects and for action recognition, or in form of flow to address behaviour analysis in crowded…

Computer Vision and Pattern Recognition · Computer Science 2015-09-30 Eduardo M. Pereira , Jaime S. Cardoso , Ricardo Morla

We establish universal approximation theorems for infinite-dimensional geometric rough paths, i.e., we show that continuous functions on the space of infinite-dimensional weakly geometric H\"older continuous rough paths can be approximated…

Probability · Mathematics 2026-03-04 Sonja Cox , Asma Khedher , Thijs Maessen

In this paper we study continuous-time quantum walks on Cayley graphs of the symmetric group, and prove various facts concerning such walks that demonstrate significant differences from their classical analogues. In particular, we show that…

Quantum Physics · Physics 2007-05-23 Heath Gerhardt , John Watrous

We study the generalized graph splines introduced by Gilbert, Tymoczko, and Viel and focus on an attribute known as the Universal Difference Property (UDP). We prove that paths, trees, and cycles satisfy UDP. We explore UDP on graphs pasted…

We describe a technique to determine the automorphism group of a geometrically represented graph, by understanding the structure of the induced action on all geometric representations. Using this, we characterize automorphism groups of…

Combinatorics · Mathematics 2015-08-05 Pavel Klavík , Peter Zeman

We consider random walks and L\'evy processes in a homogeneous group $G$. For all $p > 0$, we completely characterise (almost) all $G$-valued L\'evy processes whose sample paths have finite $p$-variation, and give sufficient conditions…

Probability · Mathematics 2018-06-18 Ilya Chevyrev

Change points in real-world systems mark significant regime shifts in system dynamics, possibly triggered by exogenous or endogenous factors. These points define regimes for the time evolution of the system and are crucial for understanding…

Machine Learning · Statistics 2025-09-30 Ioanna-Yvonni Tsaknaki , Fabrizio Lillo , Piero Mazzarisi

Cyber-physical systems of today are generating large volumes of time-series data. As manual inspection of such data is not tractable, the need for learning methods to help discover logical structure in the data has increased. We propose a…

Evaluating time series attribution methods is difficult because real-world datasets rarely provide ground truth for which time points drive a prediction. A common workaround is to generate synthetic data where class-discriminating features…

Machine Learning · Computer Science 2026-03-10 Gregor Baer

Graph neural networks (GNNs) have evolved into one of the most popular deep learning architectures. However, GNNs suffer from over-smoothing node information and, therefore, struggle to solve tasks where global graph properties are…

Machine Learning · Computer Science 2023-08-31 Bernhard Schäfl , Lukas Gruber , Johannes Brandstetter , Sepp Hochreiter

Hyperproperties, as introduced by Clarkson and Schneider, characterize the correctness of a computer program as a condition on its set of computation paths. Standard temporal logics can only refer to a single path at a time, and therefore…

Logic in Computer Science · Computer Science 2013-07-01 Bernd Finkbeiner , Markus N. Rabe , César Sánchez

This paper establishes a comprehensive concentration theory for truncated signatures of Gaussian rough paths. The signature of a path, defined as the collection of all iterated integrals, provides a complete description of its geometric…

Probability · Mathematics 2025-12-11 Atef Lechiheb

Point signatures based on the Laplacian operators on graphs, point clouds, and manifolds have become popular tools in machine learning for graphs, clustering, and shape analysis. In this work, we propose a novel point signature, the power…

Machine Learning · Statistics 2025-03-17 Karamatou Yacoubou Djima , Ka Man Yim