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We introduce Tree-AMP, standing for Tree Approximate Message Passing, a python package for compositional inference in high-dimensional tree-structured models. The package provides a unifying framework to study several approximate message passing algorithms ...
Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power ...
Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...
The conditional mean is a fundamental and important quantity whose applications include the theories of estimation and rate-distortion. It is also notoriously difficult to work with. This paper establishes novel bounds on the differential entropy of the co ...
In sensed buildings, information related to occupant movement helps optimize important func-tionalities such as caregiving, energy management, and security enhancement. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. Th ...
Nowadays, efficient and remote health monitoring is becoming increasingly important, given both the ageing of population and the combined action of an increase in obesity level and cardiovascular diseases. The healthcare industry is becoming more reliant o ...
This paper considers an additive Gaussian noise channel with arbitrarily distributed finite variance input signals. It studies the differential entropy of the minimum mean-square error (MMSE) estimator and provides a new lower bound which connects the diff ...
The Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) aims to improve constraints on the dark energy equation of state through measurements of large-scale structure at high redshift (0.8 < z < 2.5), while serving as a state-of-the-art fast radio ...
Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...
Objective. Among the different approaches for denoising neural signals, wavelet-based methods are widely used due to their ability to reduce in-band noise. All wavelet denoising algorithms have a common structure, but their effectiveness strongly depends o ...