Which Distributed Averaging Algorithm Should I Choose for my Sensor Network?

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Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces betw ...

Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

Static and mobile sensor nodes can be employed in gas monitoring tasks to detect gas leaks in an early stage and localize gas sources. Due to the intermittent nature of gas plumes and the slow dynamics of commonly used gas sensors, measuring gas concentrat ...

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

In this work we consider solutions to stochastic partial differential equations with transport noise, which are known to converge, in a suitable scaling limit, to solution of the corresponding deterministic PDE with an additional viscosity term. Large devi ...

The landscape of computing is changing, thanks to the advent of modern networking equipment that allows machines to exchange information in as little as one microsecond. Such advancement has enabled microsecond-scale distributed computing, where entire dis ...

Diffusion is one of the most important phenomena studied in science ranging from physics to biology and, in abstract form, even in social sciences. In the field of materials science, diffusion in crystalline solids is of particular interest as it plays a p ...

Successful application of diffusion chronometry is based on detailed knowledge of diffusion parameters obtained from laboratory experiments, which also need to be upscaled to be applied to natural samples. While generally applicable, several examples of di ...

Connected and autonomous vehicles (CAV) have seen a rapid development over the past decade. However, wide diffusion of high level CAVs is still decades to come, and will depend on many technological, policy and public acceptance factors. Merging a traditio ...

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

The dynamical properties of water molecules confinedin the unidirectionalhydrophilic nanopores of AlPO4-54 are investigated withquasi-elastic neutron scattering as a function of temperature downto 118 K. AlPO4-54 has among the largest pores known foralumin ...

We provide a theoretical description of dynamical heterogeneities in glass-forming liquids, based on the premise that relaxation occurs via local rearrangements coupled by elasticity. In our framework, the growth of the dynamical correlation length e and o ...

Total Flow Analysis (TFA) is a method for the worst-case analysis of time-sensitive networks. It uses service curve characterizations of the network nodes and arrival curves of flows at their sources; for tractability, the latter are often taken to be line ...

This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...

The Obukhov-Corrsin theory of scalar turbulence [21, 54] advances quantitative predictions on passive-scalar advection in a turbulent regime and can be regarded as the analogue for passive scalars of Kolmogorov's K41 theory of fully developed turbulence [4 ...

Which Distributed Averaging Algorithm Should I Choose for my Sensor Network?

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Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields

Residual-based attention in physics-informed neural networks

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

Stochastic pairwise preference convergence in Bayesian agents

Design and Evaluation of Modular Gas and Wind Sensing Nodes for Static and Mobile Deployments

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Functional data analysis with rough sample paths?

Distributional Regression and Autoregression via Optimal Transport

LDP and CLT for SPDEs with transport noise

Reliable Microsecond-Scale Distributed Computing

Atomic scale volume and grain boundary diffusion elucidated by in situ STEM

Diffusion timescale conundrum in contact metamorphism: Oxygen isotope and trace element profiles in dolomite

Diffusion of connected and autonomous vehicles concerning mode choice, policy interventions and sustainability impacts: A system dynamics modelling study

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Low-Temperature Dynamics of Water Confined in Unidirectional Hydrophilic Zeolite Nanopores

Scaling Description of Dynamical Heterogeneity and Avalanches of Relaxation in Glass-Forming Liquids

Efficient and Accurate Handling of Periodic Flows in Time-Sensitive Networks

Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

Anomalous Dissipation and Lack of Selection in the Obukhov-Corrsin Theory of Scalar Turbulence