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Choreographic programming is a paradigm where a concurrent or distributed system is developed in a top-down fashion. Programs, called choreographies, detail the desired interactions between processes, and can be compiled to distributed…

Programming Languages · Computer Science 2023-05-01 Luís Cruz-Filipe , Eva Graversen , Fabrizio Montesi , Marco Peressotti

For an autonomous linear time-invariant (LTI) system, a distributed observer with time-triggered periodic observations and event-triggered communication is proposed to estimate the state of the system. It is shown that the sampling period…

Systems and Control · Electrical Eng. & Systems 2023-05-08 Shimin Wang , Zhan Shu , Tongwen Chen

Real world systems of interest often feature interactions between discrete and continuous dynamics. Various hybrid system formalisms have been used to model and analyze this combination of dynamics, ranging from mathematical descriptions,…

Logic in Computer Science · Computer Science 2021-09-22 Yong Kiam Tan , André Platzer

Information-theoretic arguments focus on modeling the reliability of information transmission, assuming availability of infinite data at sources, thus ignoring randomness in message generation times at the respective sources. However, in…

Networking and Internet Architecture · Computer Science 2009-09-29 K. C. V. Kalyanarama Sesha Sayee

A recent study of bugs in real-world concurrent and distributed systems found that, while implementations of individual protocols tend to be robust, the composition of multiple protocols and its interplay with internal computation is the…

Programming Languages · Computer Science 2017-08-09 Luís Cruz-Filipe , Fabrizio Montesi

Delays in biological systems may be used to model events for which the underlying dynamics cannot be precisely observed. Mathematical modeling of biological systems with delays is usually based on Delay Differential Equations (DDEs), a kind…

Quantitative Methods · Quantitative Biology 2009-10-08 Roberto Barbuti , Giulio Caravagna , Paolo Milazzo , Andrea Maggiolo-Schettini

Diffusion-based generative models use stochastic differential equations (SDEs) and their equivalent ordinary differential equations (ODEs) to establish a smooth connection between a complex data distribution and a tractable prior…

Machine Learning · Computer Science 2024-08-25 Defang Chen , Zhenyu Zhou , Can Wang , Chunhua Shen , Siwei Lyu

We present a system for Complex Event Recognition (CER) based on automata. While multiple such systems have been described in the literature, they typically suffer from a lack of clear and denotational semantics, a limitation which often…

Formal Languages and Automata Theory · Computer Science 2024-07-04 Elias Alevizos , Alexander Artikis , Georgios Paliouras

In this perspective article, we discuss the scenario of dynamically emergent correlation (DEC) arising in classical and quantum noninteracting systems when they are subjected to a common fluctuating stochastic environment. The key property…

Statistical Mechanics · Physics 2026-03-04 Satya N. Majumdar , Gregory Schehr

We present Dynamic Condition Response Graphs (DCR Graphs) as a declarative, event-based process model inspired by the workflow language employed by our industrial partner and conservatively generalizing prime event structures. A dynamic…

Logic in Computer Science · Computer Science 2011-10-20 Thomas T. Hildebrandt , Raghava Rao Mukkamala

We consider the distributed leader-follower consensus problem with event-triggered communications. The system under consideration is a non-linear input-affine multi agent system. The agents are assumed to have identical dynamics structure…

Optimization and Control · Mathematics 2023-03-06 Mathieu Marchand , Vincent Andrieu , Sylvain Bertrand , Hélène Piet-Lahanier

Modern machine learning tools such as deep neural networks (DNNs) are playing a revolutionary role in many fields such as natural language processing, computer vision, and the internet of things. Once they are trained, deep learning models…

Machine Learning · Computer Science 2022-01-19 Arjun Parthasarathy , Bhaskar Krishnamachari

We argue that diffusion models' success in modeling complex distributions is, for the most part, coming from their input conditioning. This paper investigates the representation used to condition diffusion models from the perspective that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Samuel Lavoie , Michael Noukhovitch , Aaron Courville

Fault-tolerant distributed algorithms are central for building reliable spatially distributed systems. Unfortunately, the lack of a canonical precise framework for fault-tolerant algorithms is an obstacle for both verification and…

Formal Languages and Automata Theory · Computer Science 2012-10-16 Annu John , Igor Konnov , Ulrich Schmid , Helmut Veith , Josef Widder

Time delays are ubiquitous in industry and nature, and they significantly affect both transient dynamics and stability properties. Consequently, it is often necessary to identify and account for the delays when, e.g., designing a…

Dynamical Systems · Mathematics 2024-05-14 Tobias K. S. Ritschel , John Wyller

The term behavior engineering (BE) encompasses a broad integration of behavioral and compositional requirements needed to model large-scale systems. BE forms a connection between systems-engineering processes and software-engineering…

Software Engineering · Computer Science 2021-01-06 Sabah Al-Fedaghi

In this paper, we consider a network of processors aiming at cooperatively solving mixed-integer convex programs subject to uncertainty. Each node only knows a common cost function and its local uncertain constraint set. We propose a…

Optimization and Control · Mathematics 2022-07-19 Mohammadreza Chamanbaz , Giuseppe Notarstefano , Francesco Sasso , Roland Bouffanais

We study large-scale distributed cooperative systems that use optimistic replication. We represent a system as a graph of actions (operations) connected by edges that reify semantic constraints between actions. Constraint types include…

Databases · Computer Science 2007-10-08 Pierre Sutra , Marc Shapiro , João Pedro Barreto

Chain Event Graphs (CEGs) are a family of event-based graphical models that represent context-specific conditional independences typically exhibited by asymmetric state space problems. The class of continuous time dynamic CEGs (CT-DCEGs)…

Artificial Intelligence · Computer Science 2020-06-30 Aditi Shenvi , Jim Q. Smith

Systems whose time evolutions are entirely deterministic can nevertheless be studied probabilistically, i.e. in terms of the evolution of probability distributions rather than individual trajectories. This approach is central to the…

Dynamical Systems · Mathematics 2019-09-06 S. Richard Taylor