Independent component analysis is a probabilistic method for learning a linear transform of
a random vector. The goal is to find components that are maximally independent and non …

The goal of causal representation learning is to find a representation of data that consists of
causally related latent variables. We consider a setup where one has access to data from …

The latest generation of synthetic aperture radar satellites produce measurements of ground
deformation at the majority of the world's subaerial active volcanoes and can be used to …

Visual working memory (VWM) relies on sustained neural activities that code information via
various oscillatory frequencies. Previous studies, however, have emphasized time …

A challenge in the analysis of multitemporal interferometric synthetic aperture radar (InSAR)
data is distinguishing and separating volcanic, tectonic, and anthropogenic displacements …

Objective. Human facial muscle activation underlies highly sophisticated signaling
mechanisms that are critically important for healthy physiological function. Accordingly, the …

We studied with functional magnetic resonance imaging (fMRI) differences in resting-state
networks between patients with mesial temporal lobe epilepsy (MTLE) and healthy subjects …

Recent research proposed that the slowing of individual alpha frequency (IAF) could be an
objective marker of pain. However, it is unclear whether this research can fully address the …

This book is devoted to the application of advanced signal processing on event-related
potentials (ERPs) in the context of electroencephalography (EEG) for the cognitive …

We developed a data-driven method to spatiotemporally and spectrally characterize the
dynamics of brain oscillations in resting-state magnetoencephalography (MEG) data. The …