Publications related to Estimating interdependences in networks of weakly coupled deterministic systems

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Aude Billard, Mikhail Koptev, Nadia Barbara Figueroa Fernandez

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Sage Publications Ltd2024

Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Aude Billard, Bernardo Fichera

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded in order to handl ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Colin Neil Jones, Roland Schwan, Melanie Nicole Zeilinger, Xuan Truong Nghiem

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

IEEE2023

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia

Photoplethysmography (PPG) is a widely emerging method to assess vascular health in humans. The origins of the signal of reflective PPG on peripheral arteries have not been thoroughly investigated. We aimed to identify and quantify the optical and biomecha ...

MDPI2023

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Nirupam Gupta

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a line ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Tensor-Based Numerical Method For Stochastic Homogenization

This paper addresses the complexity reduction of stochastic homogenization of a class of random materials for a stationary diffusion equation. A cost-efficient approximation of the correctors is obtained using a method designed to exploit quasi-periodicity ...

SIAM PUBLICATIONS2022

Method and system for determining the intention of performing a voluntary action

Olaf Blanke, Bastien Orset

The invention relates to methods and systems for determining the intention of a subject to perform a voluntary action based on the analysis of the subject's respiratory phases and neuroelectrical signals. ...

2021

On Katznelson's Question for skew product systems

Florian Karl Richter

Katznelson's Question is a long-standing open question concerning recurrence in topological dynamics with strong historical and mathematical ties to open problems in combinatorics and harmonic analysis. In this article, we give a positive answer to Katznel ...

2021

Estimating interdependences in networks of weakly coupled deterministic systems

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Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Efficient Continual Finite-Sum Minimization

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Tensor-Based Numerical Method For Stochastic Homogenization

Method and system for determining the intention of performing a voluntary action

On Katznelson's Question for skew product systems

Efficient Continual Finite-Sum Minimization

On Katznelson's Question for skew product systems

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Tensor-Based Numerical Method For Stochastic Homogenization

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Method and system for determining the intention of performing a voluntary action

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations