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Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...
The study of dynamically propagating rupture along interfaces is of prime importance in various fields and system sizes, including tribology (nm to m), engineering (mm to m) and geophysics (m to km) (Armstrong-Hélouvry et al., 1994; Ben-Zion, 2008; Vanossi ...
We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of Optimal Control Problems (OCPs) constrained by random partial differential equ ...
This collection of essays, all authored and curated by Tim Waterman, foregrounds the entangled nature of utopia(nism), landscape (aka landship), design and imagination, where ‘everything is connected, everything is inseparable, everything can have differen ...
The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...
The Rhône River, second largest in Switzerland, has already been corrected twice (1863-1893; 1930-1960) to ensure safety and economic development in the Rhône valley. However, in October 2000, the highest flood of the century occurred showing the limitatio ...
Numerous process integration techniques were proved to be highly effective for identifying and estimating potential energy savings in the industry. However, they require high time and effort to collect and analyse process data. As a result, they do not con ...
The complexity of many-body quantum wave functions is a central aspect of several fields of physics and chemistry where nonperturbative interactions are prominent. Artificial neural networks (ANNs) have proven to be a flexible tool to approximate quantum m ...
We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying the knockoff distribution requires solving a large-scale semidefinite progra ...