Publications associées à Morphological component analysis for sparse regularization in plane wave imaging

Efficient local linearity regularization to overcome catastrophic overfitting

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Elias Abad Rocamora

Catastrophic overfitting (CO) in single-step adversarial training (AT) results in abrupt drops in the adversarial test accuracy (even down to 0%). For models trained with multi-step AT, it has been observed that the loss function behaves locally linearly w ...

2024

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Pakshal Narendra Bohra

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Optothermal shaping of lamb waves with square and spiral phase fronts

Romain Christophe Rémy Fleury, Aleksi Antoine Bossart, Janez Rus

We introduce a Lamb-wave medium with tunable propagation velocities, which are controlled by a two-dimensional heating pattern produced by a laser beam. We utilized it to demonstrate that waves in an appropriately designed medium can propagate in the form ...

2024

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Volkan Cevher, Fanghui Liu

This paper studies kernel ridge regression in high dimensions under covariate shifts and analyzes the role of importance re-weighting. We first derive the asymptotic expansion of high dimensional kernels under covariate shifts. By a bias-variance decomposi ...

2024

Oblique streaming waves observed in multipactor-induced plasma discharge above a dielectric surface

Guang-Yu Sun, Haomin Sun

In a recent discovery (Wen et al 2022 Phys. Rev. Lett. 129 045001), streaming waves were found in multipactor-induced plasma discharges. However, due to the limitations of a 1D simulation setup, these waves displayed only transverse dynamics. In this lette ...

2024

Multi-Frequency Tracking via Group-Sparse Optimal Transport

Isabel Haasler

In this letter, we introduce an optimal transport framework for inferring power distributions over both spatial location and temporal frequency. Recently, it has been shown that optimal transport is a powerful tool for estimating spatial spectra that chang ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Optimization of elastic wave propagation in a reconfigurable medium by genetic algorithms with adaptive mutation probability

Romain Christophe Rémy Fleury, Janez Rus

We introduce a reconfigurable medium for the manipulation of elastic propagation properties of Lamb waves. It is based on a shape memory polymer (SMP) with temperature-dependent Young's modulus. Waves are excited by a laser pulse and detected by a laser vi ...

IOP Publishing Ltd2023

A Neural-Network-Based Convex Regularizer for Inverse Problems

Michaël Unser, Stanislas Ducotterd, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer

The emergence of deep-learning-based methods to solve image-reconstruction problems has enabled a significant increase in quality. Unfortunately, these new methods often lack reliability and explainability, and there is a growing interest to address these ...

2023

Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Fast camera imaging is used to study ion acoustic waves propagating azimuthally in a magnetized plasma column. The high-speed image sequences are analyzed using proper orthogonal decomposition and 2D Fourier transform, allowing to evaluate the assets and d ...

2023

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Scott William Pesme, Nicolas Henri Bernard Flammarion, Mathieu Even

In this paper, we investigate the impact of stochasticity and large stepsizes on the implicit regularisation of gradient descent (GD) and stochastic gradient descent (SGD) over diagonal linear networks. We prove the convergence of GD and SGD with macroscop ...

2023

Experimental study on velocity distributions, secondary currents, and coherent structures in open channel flow with submerged riparian vegetation

Haoran Shi

Riparian vegetation, which is commonly found in natural rivers and open channels, has a strong influence on flow structures. This paper describes a laboratory experiment on velocity distributions, secondary currents, and coherent structures in narrow open- ...

ELSEVIER SCI LTD2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Hugo Chao Cui, Florent Gérard Krzakala, Lenka Zdeborová

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Regularization of polynomial networks for image recognition

Volkan Cevher, Bohan Wang, Grigorios Chrysos

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

2023

Regularization of polynomial networks for image recognition

Volkan Cevher, Bohan Wang, Grigorios Chrysos

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

Ieee Computer Soc2023

Regularization Techniques for Low-Resource Machine Translation

Alejandro Ramírez Atrio

Neural machine translation (MT) and text generation have recently reached very high levels of quality. However, both areas share a problem: in order to reach these levels, they require massive amounts of data. When this is not present, they lack generaliza ...

EPFL2023

Long-distance coherent propagation of magnon polarons in a ferroelectric-ferromagnetic heterostructure

Jean-Philippe Ansermet, Haiming Yu, Peng Chen, Song Liu, Jilei Chen, Jianyu Zhang, Jinlong Wang, Yao Zhang

We experimentally demonstrate the coherent propagation of magnon polarons, the hybridized excitations formed by the coupling of spin waves and Rayleigh/Love surface acoustic waves, in a heterostructure consisting of ferroelectric BaTiO3 and ferromagnetic L ...

Amer Physical Soc2023

Spin wave dispersion of ultra-low damping hematite (α-Fe2O3) at GHz frequencies

Dirk Grundler, Ferdinand Rémy Hynek Posva, Mohammad Hamdi

Raw data associated to the manuscript ‘’Spin wave dispersion of ultra-low damping hematite (α-Fe2O3) at GHz frequencies‘’, Physical Review Materials 7, 054407(2023); doi: 10.1103/PhysRevMaterials.7.054407 Information about file fo ...

Zenodo2023

Spin wave dispersion of ultra-low damping hematite ( α−Fe2O3 ) at GHz frequencies

Dirk Grundler, Ferdinand Rémy Hynek Posva, Mohammad Hamdi

Low magnetic damping and high group velocity of spin waves (SWs) or magnons are two crucial parameters for functional magnonic devices. Magnonics research on signal processing and wave-based computation at GHz frequencies focused on the artificial ferrimag ...

2023

Toward Metantennas: Metamaterial-Based Antennas for Wireless Communications

Yuanyan Su

Antennas have historically been the most common electromagnetic (EM) technology for wireless communication systems. Antenna as hardware is entirely dependent on the EM properties of the materials used, mostly related to the permittivity and permeability. I ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Jian Zhou, Olga Fink

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...

2023