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Parametrised quantum circuits are a central framework for near term quantum machine learning. However, it remains challenging to determine in advance how architectural choices, such as encoding strategies, gate placement, and entangling…

Quantum Physics · Physics 2026-04-07 Kyle James Stuart Campbell , Luigi Del Debbio , Petros Wallden

The performance of a language model has been shown to be effectively modeled as a power-law in its parameter count. Here we study the scaling behaviors of Routing Networks: architectures that conditionally use only a subset of their…

Networked structures arise in a wide array of different contexts such as technological and transportation infrastructures, social phenomena, and biological systems. These highly interconnected systems have recently been the focus of a great…

Statistical Mechanics · Physics 2009-11-10 Alain Barrat , Marc Barthelemy , Romualdo Pastor-Satorras , Alessandro Vespignani

We review the main tools which allow for the statistical characterization of weighted networks. We then present two case studies, the airline connection network and the scientific collaboration network, which are representative of critical…

Statistical Mechanics · Physics 2009-11-10 Marc Barthelemy , Alain Barrat , Romualdo Pastor-Satorras , Alessandro Vespignani

Mixed reality (MR) environments offer embodied spatial interaction, providing intuitive 3D manipulation capabilities that enhance the conceptual design process. Parametric modeling, a powerful and advanced architectural design method,…

Human-Computer Interaction · Computer Science 2025-06-09 Ruochen Ji , Lyu Tiangang

Quantum communication systems harness modern physics through state-of-the-art optical engineering to provide revolutionary capabilities. An important concern for quantum communication engineering is designing and prototyping these systems…

Quantum Physics · Physics 2014-10-21 Travis S. Humble , Ronald J. Sadlier

Enterprise modeling deals with the increasing complexity of processes and systems by operationalizing model content and by linking complementary models and languages, thus amplifying the model-value beyond mere comprehensible pictures. To…

Software Engineering · Computer Science 2022-03-29 Victoria Döller

Mechanistic interpretability seeks to localize model behavior to the internal components that causally realize it. Prior work has advanced activation-space localization and causal tracing, but modules that appear important in activation…

Artificial Intelligence · Computer Science 2026-04-16 Chenghao Sun , Chengsheng Zhang , Guanzheng Qin , Rui Dai , Xinmei Tian

In this article, a new generic higher-order finite-element framework for massively parallel simulations is presented. The modular software architecture is carefully designed to exploit the resources of modern and future supercomputers.…

Mathematical Software · Computer Science 2018-05-28 Nils Kohl , Dominik Thönnes , Daniel Drzisga , Dominik Bartuschat , Ulrich Rüde

A quantitative model of concurrent interaction is introduced. The basic objects are linear combinations of partial order relations, acted upon by a group of permutations that represents potential non-determinism in synchronisation. This…

Logic in Computer Science · Computer Science 2011-07-08 Emmanuel Beffara

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions…

Machine Learning · Computer Science 2010-06-29 Shankar Vembu

Parametric Computer-aided design (CAD) enables the creation of reusable models by integrating variables into geometric properties, facilitating customization without a complete redesign. However, creating parametric designs in…

Human-Computer Interaction · Computer Science 2024-08-06 J. Felipe Gonzalez , Thomas Pietrzak , Audrey Girouard , Géry Casiez

Software is a communication system. The usual topic of communication is program behavior, as encoded by programs. Domain-specific libraries are codebooks, domain-specific languages are coding schemes, and so forth. To turn metaphor into…

Software Engineering · Computer Science 2007-07-30 Todd L. Veldhuizen

We present a Bayesian formulation of weighted stochastic block models that can be used to infer the large-scale modular structure of weighted networks, including their hierarchical organization. Our method is nonparametric, and thus does…

Machine Learning · Statistics 2018-01-24 Tiago P. Peixoto

Today, data guides the decision-making process of most companies. Effectively analyzing and manipulating data at scale to extract and exploit relevant knowledge is a challenging task, due to data characteristics such as its size, the rate…

Software Engineering · Computer Science 2025-03-24 Arianna Dragoni , Alessandro Margara

Developing applications considering reactiveness, scalability and re-usability has always been at the center of attention of robotic researchers. Behavior-based architectures have been proposed as a programming paradigm to develop robust…

Robotics · Computer Science 2021-06-30 Ali Paikan , Giorgio Metta , Lorenzo Natale

Multiobjective combinatorial optimization deals with problems considering more than one viewpoint or scenario. The problem of aggregating multiple criteria to obtain a globalizing objective function is of special interest when the number of…

Optimization and Control · Mathematics 2013-06-07 Elena Fernández , Miguel A. Pozo , Justo Puerto

Component-oriented and service-oriented approaches have gained a strong enthusiasm in industries and academia with a particular interest for service-oriented approaches. A component is a software entity with given functionalities, made…

Software Engineering · Computer Science 2009-10-13 Christian Attiogbe

This paper formalises the literature on emerging design patterns and paradigms for Large Language Model (LLM)-enabled multi-agent systems (MAS), evaluating their practical utility across various domains. We define key architectural…

Multiagent Systems · Computer Science 2026-01-08 Harri Renney , Maxim N Nethercott , Nathan Renney , Peter Hayes

We may attempt to encapsulate what we know about a physical system by a model structure, $S$. This collection of related models is defined by parametric relationships between system features; say observables (outputs), unobservable…

Methodology · Statistics 2021-02-16 Jason M. Whyte
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