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Concept

Independent component analysis

Related publications (29)

Effects of eight neuropsychiatric copy number variants on human brain structure

Lester Melie Garcia, Borja Rodriguez Herreros

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing ...

SPRINGERNATURE2021

A Self-powered Ambient Light Power Measurement Platform with Time-domain Readout

Catherine Dehollain, Roberto La Rosa

Internet of Things (IoT) provides more and more adequate infrastructures for many applications and advanced services. This scenario promotes the ability to satisfy the growing demand for innovative measuring systems, increasingly popular consisting of inte ...

IEEE2021

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Erixhen Sula

Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...

EPFL2021

Compact atomic descriptors enable accurate predictions via linear models

Kevin Rossi

We probe the accuracy of linear ridge regression employing a three-body local density representation derived from the atomic cluster expansion. We benchmark the accuracy of this framework in the prediction of formation energies and atomic forces in molecul ...

AIP Publishing2021

Lamellar carbon-aluminosilicate nanocomposites with macroscopic orientation

Anna Fontcuberta i Morral, Emad Oveisi, Holger Frauenrath, Yannik Fontana, Enzo Jean Raymond Bomal, Dragana Paripovic

Novel preparative approaches towards lamellar nanocomposites of carbon and inorganic materials are relevant for a broad range of technological applications. Here, we describe how to utilize the co-assembly of a liquid-crystalline hexaphenylene amphiphile a ...

ROYAL SOC CHEMISTRY2021

Common Information Components Analysis

Michael Christoph Gastpar, Erixhen Sula

We give an information-theoretic interpretation of Canonical Correlation Analysis (CCA) via (relaxed) Wyner's common information. CCA permits to extract from two high-dimensional data sets low-dimensional descriptions (features) that capture the commonalit ...

IEEE2020

Principal Component Analysis By Optimization Of Symmetric Functions Has No Spurious Local Optima

Armin Eftekhari

Principal component analysis (PCA) finds the best linear representation of data and is an indispensable tool in many learning and inference tasks. Classically, principal components of a dataset are interpreted as the directions that preserve most of its "e ...

SIAM PUBLICATIONS2020

Structure-property maps with Kernel principal covariates regression

Michele Ceriotti, Guillaume André Jean Fraux, Benjamin Aaron Helfrecht, Rose Kathleen Cersonsky-Adorf

Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building supervised or unsupervised machine learning models. Principal covariates regression (PC ...

2020

The 3D Smith Chart: From Theory to Experimental Reality

Mihai Adrian Ionescu, Andrei Müller

The Smith chart was primarily developed, extended, and refined by Phillip Hagar Smith [1] in a series of works published [2]-[4] between 1939 and 1969. Smith was born in Lexington, Massachusetts, in 1905. He majored in electrical communications at Tufts Un ...

2020