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Publications associées (104)

Development of a semi-implicit contact methodology for finite volume stress solvers

Andreas Pautz, Carlo Fiorina, Alessandro Scolaro

The past decades have seen numerous efforts to apply the finite volume methodology to solid mechanics problems. However, only limited work has been done by the finite volume community toward the simulation of mechanical contact. In this article, we present ...

WILEY2021

Wavelet-Fourier CORSING techniques for multidimensional advection-diffusion-reaction equations

Fabio Nobile, Simone Brugiapaglia

We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection–diffusion–reaction equations based on the COmpRessed SolvING (CORSING) paradigm. Combining the Petrov–Galerkin technique with the compressed ...

2020

TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

Pascal Fua, Mateusz Kozinski, Leonardo Citraro, Subeesh Vasu

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

2020

Toward a Dynamic Threshold for Quality-Score Distortion in Reference-Based Alignment

Marco Mattavelli, Claudio Paolo Alberti, Ana Angelica Hernandez Lopez

The intrinsic high entropy metadata, known as quality scores, are largely the cause of the substantial size of sequence data files. Yet, there is no consensus on a viable reduction of the resolution of the quality score scale, arguably because of collatera ...

2019

On the relevance of quality score metadata in genomic sequence data for omics applications

Ana Angelica Hernandez Lopez

High-throughput sequencing of DNA molecules has revolutionized biomedical research by enabling the quantitative analysis of the genome to study its function, structure and dynamics. It is driving sequencing-based experiments in life sciences as evidenced b ...

EPFL2019

Diffusion Learning In Non-Convex Environments

Ali H. Sayed, Stefan Vlaski

Driven by the need to solve increasingly complex optimization problems in signal processing and machine learning, recent years have seen rising interest in the behavior of gradient-descent based algorithms in non-convex environments. Most of the works on d ...

IEEE2019

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

Pascal Frossard, Arun Venkitaraman

In presence of sparse noise we propose kernel regression for predicting output vectors which are smooth over a given graph. Sparse noise models the training outputs being corrupted either with missing samples or large perturbations. The presence of sparse ...

IEEE2019

Approximate Cloaking via Transformation Optics for Electromagnetic Waves

Xuan Loc Tran

Cloaking via transformation optics was introduced by Pendry, Schurig, and Smith for the Maxwell system and Leonhardt in the geometric optics setting. They used a singular change of variables which blows up a point into a cloaked region. The same transforma ...

EPFL2018

Optimal Lagrange Multipliers for Dependent Rate Allocation in Video Coding

Pascal Frossard, Ana Karina De Abreu Goes

In a typical video rate allocation problem, the objective is to optimally distribute a source rate budget among a set of (in)dependently coded data units to minimize the total distortion. Conventional Lagrangian approaches convert the lone rate constraint ...

Elsevier2018

Machine learning-based tools to model and to remove the off-target effect

François Fleuret

A RNA interference, also called a gene knockdown, is a biological technique which consists of inhibiting a targeted gene in a cell. By doing so, one can identify statistical dependencies between a gene and a cell phenotype. However, during such a gene inhi ...

Springer2017

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