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 ...
Mid-infrared (mid-IR) observations are powerful in identifying heavily obscured active galactic nuclei (AGN) that have weak emission in other wavelengths. Data from the Mid-Infrared Instrument (MIRI) on board the James Webb Space Telescope provides an exce ...
Line ratio diagnostics provide valuable clues as to the source of ionizing radiation in galaxies with intense black hole accretion and starbursting events, such as local Seyfert galaxies or galaxies at the peak of their star formation history. We aim to pr ...
Ion transport through biological and solid-state nanochannels is known to be a highly noisy process. The power spectrum of current fluctuations is empirically known to scale like the inverse of frequency, following the long-standing yet poorly understood H ...
In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model upd ...
Free-electron lasers and high-harmonic-generation table-top systems are new sources of extreme-ultraviolet to hard X-ray photons, providing ultrashort pulses that are intense, coherent and tunable. They are enabling a broad range of nonlinear optical and s ...
Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...
The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of similar to 10, improving the sample statistics to study the early chemical evolution of the Mil ...
This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...
The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...
Carbon K-edge resonant Auger spectra of gas-phase allene following excitation of the pre-edge 1s -> pi* transitions are presented and analysed with the support of EOM-CCSD/cc-pVTZ calculations. X-Ray absorption (XAS), X-ray photoelectron (XPS), valence ban ...
A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...
