Natural organic matter, including humic substances (HS), comprises complex secondary
structures with no defined covalent chemical bonds and stabilized by inter-and intra …

This paper describes a new MATLAB software package of iterative regularization methods
and test problems for large-scale linear inverse problems. The software package, called IR …

Deep-learning methods have gained widespread popularity for effectively suppressing
random noise in seismic data. The recent progress in techniques based on supervised …

In the last decades, unsupervised deep learning based methods have caught researchers'
attention, since in many real applications, such as medical imaging, collecting a large …

Nuclear magnetic resonance (NMR) techniques are largely employed in several fields. As
an example, NMR spectroscopy is used to provide structural and conformational information …

Trap** phenomena degrade the dynamic performance of wide-bandgap transistors.
However, the identification of the related traps is challenging, especially in presence of non …

Abstract Deep Image Prior (DIP) is currently among the most efficient unsupervised deep
learning based methods for ill-posed inverse problems in imaging. This novel framework …

Most supervised learning methods require observation data and ground truth pairs as data
sets to train the network. However, it is difficult and time-consuming to obtain a large number …

Multi‐exponential decay is prevalent in magnetic resonance spectroscopy, relaxation, and
imaging. This paper describes simple MATLAB and Python functions and scripts for …

The surface charge accumulation at a gas-solid interface distorts the local electric field and
in turn leads to surface flashover, which restricts the development and application of high …