Publications related to Graph Neural Networks for Electric and Hydraulic Data Fusion to Enhance Short-term Forecasting of Pumped-storage Hydroelectricity

Related publications (20)

Information Propagation in Multilayer Systems with Higher-Order Interactions across Timescales

Daniel Maria Busiello, Giorgio Nicoletti

Complex systems are characterized by multiple spatial and temporal scales. A natural framework to capture their multiscale nature is that of multilayer networks, where different layers represent distinct physical processes that often regulate each other in ...

American Physical Society2024

Post stroke recovery prediction

Dimitri Nestor Alice Van De Ville, Elvira Pirondini

The present relates to a method for generating a graph representing a virtually lesioned connectome of a patient after a stroke comprising:- providing structural data of the brain of the patient after the stroke;- segmenting said structural data to delinea ...

2024

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

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

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

IEEE2024

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Silvestro Micera

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

IOP Publishing Ltd2023

Enabling renewable Europe through optimal design and operation

Alessio Santecchia

Europe is currently transitioning from fossil energy sources to renewable generation of electric power. Although fundamental to reach net-zero targets, intermittent renewables are disrupting conventional methods used in operational planning and design of p ...

EPFL2022

Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation

Qian Wang, Tobias Kober, Tom Hilbert

Objective To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patients with ...

SPRINGER2022

Targeting the frontoparietal network using bifocal transcranial alternating current stimulation during a motor sequence learning task in healthy older adults

Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Laurijn Rianne Draaisma

Background: Healthy older adults show a decrease in motor performance and motor learning capacity as well as in working memory (WM) performance. WM has been suggested to be involved in motor learning processes, such as sequence learning. Correlational evid ...

2022

Effect of the Impact Contact Duration on Machine Learning Models for Impact Position Detection

Yves Perriard, Paolo Germano, Jonathan André Jean-Marie Chavanne, Camilo Hernandez Mejia

Touch-screens have become the most common way of interaction between humans and machines. Nevertheless, the lack of rich haptic-feedback on most of the devices limits the quality and effectivity of the interaction. To develop novel haptic feedback generati ...

2020

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

Edo Collins

With ever greater computational resources and more accessible software, deep neural networks have become ubiquitous across industry and academia. Their remarkable ability to generalize to new samples defies the conventional view, which holds that complex, ...

EPFL2019

Behavioural compass: animal behaviour recognition using magnetometers

Kamiar Aminian, Pritish Chakravarty

Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of b ...

2019

Apartment Structure Estimation Using Fully Convolutional Networks and Graph Model

Jing Zhang, Jin Zhang

Apartment searching has been a hot demand all over the world. Understanding the apartment structure will significantly contribute to simplifying the searching process. In this project, the fully convolutional networks are applied to generate semantic segme ...

ASSOC COMPUTING MACHINERY2018

Exploring Feature Dimensions to Learn a New Policy in an Uninformed Reinforcement Learning Task

Oh-Hyeon Choung

When making a choice with limited information, we explore new features through trial-and-error to learn how they are related. However, few studies have investigated exploratory behaviour when information is limited. In this study, we address, at both the b ...

Springer Nature2017

Design optimization of electrical hubs using hybrid evolutionary algorithm

Jean-Louis Scartezzini, Dasaraden Mauree, Amarasinghage Tharindu Dasun Perera, Vahid Moussavi Nik

Integration of non-dispatchable renewable energy sources such as wind and solar into the grid is challenging due to the stochastic nature of energy sources. Hence, electrical hubs (EH) and virtual power plants that combine non-dispatchable energy sources, ...

Amer Soc Mechanical Engineers2016

Energy-Efficient Co-Design Optimization of Many-Core Platforms for Big-Data Streaming Applications

Karim Kanoun

Big-Data streaming applications are used in several domains such as social media analysis, financial analysis, video annotation, surveillance, medical services and traffic prediction. These applications, running on different types of platforms from mobile ...

EPFL2015

Exploring Deviation in Inquiry Learning: Degrees of Freedom or Source of Problems?

Denis Gillet, Maria Jesus Rodriguez Triana

The European Go-Lab project aims to promote Inquiry-based Learning (IBL) with online laboratories. To support teachers and students in this endeavor, the project provides an IBL model (a sequence of inquiry phases) as well as the technological infrastructu ...

Asia-Pacific Society for Computers in Education2015

Tutorial Session in: Large-scale hierarchical control for congested urban networks

Nikolaos Geroliminis

This tutorial describes methodologies to model and understand the collective behavior or different types of urban systems. It highlights under what physical properties the aggregated laws will provide reasonable description of congestion for single- and mu ...

Ieee2014

Object Classification and Detection in High Dimensional Feature Space

Charles Dubout

Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...

EPFL2014

Adaptive sensorimotor peripersonal space representation and motor learning for a humanoid robot

Micha Hersch

This thesis presents possible computational mechanisms by which a humanoid robot can develop a coherent representation of the space within its reach (its peripersonal space), and use it to control its movements. Those mechanisms are inspired by current the ...

EPFL2009

Error and Attack Tolerance of Layered Complex Networks

Patric Hagmann, Patrick Thiran, Maciej Kurant

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect w ...

2007

Information Flow Decomposition for Network Coding

Christina Fragouli

The famous min-cut, max-flow theorem states that a source node can send a commodity through a network to a sink node at the rate determined by the flow of the min-cut separating the source and the sink. Recently it has been shown that by linear re-encoding ...

2006