Publications associées à An estimator for the diagonal of a matrix

Publications associées (12)

Improved bounds and inference on optimal regimes

Mats Julius Stensrud, Aaron Leor Sarvet, Julien David Laurendeau

Point identification of causal effects requires strong assumptions that are unreasonable in many practical settings. However, bounds on these effects can often be derived under plausible assumptions. Even when these bounds are wide or cover null effects, t ...

Informa UK Limited2025

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Andrea Zanoni

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022

Self-Exciting Point Processes: Identification and Control

Michael Mark

This thesis addresses theoretical and practical aspects of identification and subsequent control of self-exciting point processes. The main contributions correspond to four separate scientific papers. In the first paper, we address the challenge of robust ...

EPFL2022

Sparsely Observed Functional Time Series: Theory and Applications

Tomas Rubin

Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

EPFL2021

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Giuseppe Carleo, Riccardo Rossi, Dian Wu

Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...

AMER PHYSICAL SOC2021

Weak-lensing shear measurement with machine learning Teaching artificial neural networks about feature noise

Frédéric Courbin, Malte Tewes, Nicolai Hildebrandt, Thibault Adrien Kuntzer

Cosmic shear, that is weak gravitational lensing by the large-scale matter structure of the Universe, is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe re ...

EDP SCIENCES S A2019

An anisotropic adaptive finite element algorithm for transonic viscous flows around a wing

Marco Picasso, Wissam Hassan

An adaptive finite element algorithm to compute transonic viscous flows around a wing is presented. The adaptive criteria is based on an anisotropic error estimator in the 115 semi-norm, justified for an advection-diffusion problem with stabilized finite e ...

Pergamon-Elsevier Science Ltd2015

MAP Estimators for Self-Similar Sparse Stochastic Models

Michaël Unser, Emrah Bostan, Julien René Fageot, Ulugbek Kamilov

We consider the reconstruction of multi-dimensional signals from noisy samples. The problem is formulated within the framework of the theory of continuous-domain sparse stochastic processes. In particular, we study the fractional Laplacian as the whitening ...

SampTA2013

Evolution of source EEG synchronization in early Alzheimer's disease

Reto Meuli, Cristian Carmeli, Alireza Khadivi

Alzheimer's disease (AD) disrupts functional connectivity in distributed cortical networks. We analyzed changes in the S-estimator, a measure of multivariate intraregional synchronization, in electroencephalogram (EEG) source space in 15 mild AD patients v ...

Elsevier2013

Algorithmes d'adaptation de maillages anisotropes et application à l'aérodynamique

Wissam Hassan

The goal of this thesis is to study an anisotropic adaptive algorithm for transonic compressible viscous flow around an airwing. A convection-diffusion model problem is considered, an anisotropic a posteriori error estimator for the H1 semi-norm of the err ...

EPFL2012

Image denoising by pointwise thresholding of the undecimated wavelet coefficients: A global sure optimum

Thierry Blu, Florian Luisier

We devise a new undecimated wavelet thresholding for denoising images corrupted by additive Gaussian white noise. The first key point of our approach is the use of a linearly parameterized pointwise thresholding function. The second key point consists in o ...

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