Publications associées à Reduced order models to address temporal complexity and geometrical variability in hemodynamics

Publications associées (17)

Reverse engineering primate sensorimotor control with machine learning

The ability of the brain to produce adaptive and dexterous movements relies on the seamless integration of sensory feedback into motor commands. Despite significant advances in motor neuroscience, critical gaps persist in understanding how proprioceptive a ...

EPFL2025

Mathematical Analysis and Optimization of Features for Atomistic Machine Learning

Kevin Kazuki Huguenin-Dumittan

Computational methods at the atomic scale based on machine learning have been a fruitful research field in the past decade by merging the advantages of classical and quantum mechanical approaches. While parts of the field are already reaching a mature stat ...

EPFL2025

Learning Time-Scales in Two-Layers Neural Networks

Raphaël Jean Berthier

Gradient-based learning in multi-layer neural networks displays a number of striking features. In particular, the decrease rate of empirical risk is non-monotone even after averaging over large batches. Long plateaus in which one observes barely any progre ...

2024

Partial annotations in active learning for semantic segmentation

Katrin Beyer, Radhakrishna Achanta

Semantic segmentation with deep learning plays a crucial role in various fields, including civil engineering, particularly in tasks such as damage assessment and urban planning. This paper addresses the challenge of efficiently training deep learning model ...

2024

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Wenlong Liao

Recently, remarkable progress has been made in the application of machine learning (ML) techniques (e.g., neural networks) to transformer fault diagnosis. However, the diagnostic processes employed by these techniques often suffer from a lack of interpreta ...

2024

Automated Interpretation of Lung Sounds by Deep Learning in Children With Asthma: Scoping Review and Strengths, Weaknesses, Opportunities, and Threats Analysis

Mary-Anne Hartley

Background: The interpretation of lung sounds plays a crucial role in the appropriate diagnosis and management of pediatric asthma. Applying artificial intelligence (AI) to this task has the potential to better standardize assessment and may even improve i ...

2024

Impact of arterial system alterations due to amputation on arterial stiffness and hemodynamics: a numerical study

Nikolaos Stergiopoulos

Subjects with amputation of the lower limbs are at increased risk of cardiovascular mortality and morbidity. We hypothesize that amputation-induced alterations in the arterial tree negatively impact arterial biomechanics, blood pressure and flow behavior. ...

Nature Research2024

A 2.46-mm2 Miniaturized Brain-Machine Interface (MiBMI) Enabling 31-Class Brain-to-Text Decoding

Mahsa Shoaran, Uisub Shin, Mohammad Ali Shaeri, Amitabh Yadav

Recent advancements in brain-machine interface (BMI) technology offer groundbreaking solutions for individuals with motor impairments, potentially extending to speech synthesis and handwriting assistance. However, current BMIs rely on cumbersome benchtop s ...

2024

Geometry-Driven Stock-Constrained Truss Design via Equilibrium-Based Structural Models

Corentin Jean Dominique Fivet

This paper presents a geometry-driven approach to form-finding with reused stock elements. Our proposed workflow uses a K-mean algorithm to cluster stock elements and incorporate their geometrical values early in the form-finding process. A feedback loop i ...

Springer2024

Uncertainty quantification in groundwater volume predictions from seismic data using neural networks

Jan Sickmann Hesthaven

Optimum groundwater management is important for addressing the global challenges of water scarcity, especially in arid regions. This study demonstrates the application of synthetic data combined with seismic methods to quantify water volumes in a controlle ...

European Association of Geoscientists and Engineers, EAGE2024

Neurostimulation and Wireless Data Transmission Circuits for Implantable High-Density Neural Interfaces

Cong Ding

Over the past years, implantable closed-loop neural interfaces have received increasing attention for their potential to enhance the understanding of the brain, treat neurological disorders, and provide unprecedented opportunities for individuals with para ...

EPFL2024

Modelling travel behaviour: A choice modelling perspective

Michel Bierlaire, Silvia Francesca Varotto

Choice models have been applied to explain and predict the transportation choices of individuals for half a century. The advent of big data brings about new opportunities and poses new challenges for forecasting. This chapter discusses the major methodolog ...

Edward Elgar Publishing2024

Cellpose training data and scripts from "Inhibition of CERS1 in aging skeletal muscle exacerbates age-related muscle impairments"

Johan Auwerx, Olivier Burri, Martin Rainer Wohlwend

This Workflow contains all the material necessary to reproduce the results of the QuPath analysis performed in the paper "Inhibition of CERS1 in aging skeletal muscle exacerbates age-related muscle impairments" Inside this workflow and dataset, you will f ...

Zenodo2024

Validation of SOLPS-ITER simulations against the TCV-X21 reference case

Holger Reimerdes, Christian Gabriel Theiler, Davide Galassi, Claudia Colandrea, Lorenzo Martinelli, Diego Sales de Oliveira, Ming Yin Kenneth Lee

This paper presents a quantitative validation of Scrape-Off Layer Plasma Simulation-ITER (SOLPS-ITER) simulations against the TCV-X21 reference case and provides insights into the neutral dynamics and ionization source distribution in this scenario. TCV-X2 ...

IOP Publishing Ltd2024

Design optimization of a phase-change capacitive sensor for irreversible temperature threshold monitoring and its eco-friendly and wireless implementation

Danick Briand, James Alec Pierce Bourely

Monitoring the temperature of perishable goods during transport and storage is essential to prevent waste and maintain product quality. Exploiting the unique property of phase-change materials (PCM), altering their physical state at specific temperatures, ...

Elsevier BV2024

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

Tanja Christina Käser Jacober, Vinitra Swamy, Jibril Albachir Frej

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

2023

Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods

Corinne Louise Jones

Convolutional neural networks, as most artificial neural networks, are frequently viewed as methods different in essence from kernel-based methods. In this work we translate several classical convolutional neural networks into kernel-based counterparts. Ea ...

2023