Metric Learning with Rank and Sparsity Constraints

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

Dirk Grundler, Mohammad Hamdi, Ferdinand Rémy Hynek Posva

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, Mohammad Hamdi, Ferdinand Rémy Hynek Posva

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

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

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

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

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Christian Leinenbach, Sergey Shevchik, Rafal Wróbel, Marc Leparoux

This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

Elsevier Sci Ltd2023

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Christian Robert Abbet

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

EPFL2023

Quantization for Distributed Processing and Learning of Structured Data

Isabela Cunha Maia Nobre

In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

EPFL2022

Text as signal. A tutorial with case studies focusing on social media (Twitter)

Erick Jorge Canales Rodriguez

Sentiment analysis is the automated coding of emotions expressed in text. Sentiment analysis and other types of analyses focusing on the automatic coding of textual documents are increasingly popular in psychology and computer science. However, the potenti ...

SPRINGER2022

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Aleksandra Radenovic, Andras Kis, Mukesh Kumar Tripathi, Guilherme Migliato Marega, Zhenyu Wang

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Thomas Jean Debarre

The goal of this thesis is to study continuous-domain inverse problems for the reconstruction of sparse signals and to develop efficient algorithms to solve such problems computationally. The task is to recover a signal of interest as a continuous function ...