Publications associées à Influential observation

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe highlighted the sensibility of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy system configurations to ensure energy supply stability, it is necess ...

2023

Graph Learning with Partial Observations: Role of Degree Concentration

Ali H. Sayed, Augusto José Rabelo Almeida Santos

In this work we consider the problem of learning an Erdos-Renyi graph over a diffusion network when: i) data from only a limited subset of nodes are available (partial observation); ii) and the inferential goal is to discover the graph of interconnections ...

IEEE2019

Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization

Daniel Kuhn, Napat Rujeerapaiboon, Kilian Schindler, Wolfram Wiesemann

Plain vanilla K-means clustering is prone to produce unbalanced clusters and suffers from outlier sensitivity. To mitigate both shortcomings, we formulate a joint outlier-detection and clustering problem, which assigns a prescribed number of datapoints to ...

2019

Additive Fabrication of Silicon Pillars on Monocrystalline Silicon by Direct Laser Melting

Marie Camille Laëtitia Le Dantec

Additive Manufacturing (AM) is an emerging part production technology that offers many ad-vantages such as high degree of customization, material savings and design of 3D highly complex structures. However, AM is a complex multiphysics process. Therefore, ...

EPFL2018

Inertial manipulation of bubbles in rectangular microfluidic channels

Demetri Psaltis, Pooria Hadikhani, François Gallaire, Gioele Mariano Nicolò Balestra, Miguel Antonio Modestino, Seyyed Mohammad Hosseini Hashemi, Lailai Zhu

Inertial microfluidics is an active field of research that deals with crossflow positioning of the suspended entities in microflows. Until now, the majority of the studies have focused on the behavior of rigid particles in order to provide guidelines for m ...

2018

Model-Free Methodologies for Data-Interpretation during Continuous Monitoring of Structures

Irwanda Laory

Most civil engineering infrastructures, especially bridges worldwide, are approaching the end of their designed lifespan. They are continuously deteriorating due largely to material aging, excessive loads and changing environments. Therefore, it is crucial ...

EPFL2013

Cutting Down the Energy Consumed by Domestic Robots: Insights from Robotic Vacuum Cleaners

Francesco Mondada, Philippe Rétornaz, Florian Christopher Vaussard

The market of domestic service robots, and especially vacuum cleaners, has kept growing during the past decade. According to the International Federation of Robotics, more than 1 million units were sold worldwide in 2010. Currently, there is no in-depth an ...

Springer Berlin Heidelberg2012

Robust Value at Risk Prediction

Loriano Mancini, Fabio Trojani

This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that contr ...

Oxford University Press2011

General state-space models : randomised quasi-Monte Carlo methods for general Kalman recursion

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004