With the broader and highly successful usage of machine learning (ML) in industry and the
sciences, there has been a growing demand for explainable artificial intelligence (XAI) …

Modern research in the life sciences is unthinkable without computational methods for
extracting, quantifying and visualising information derived from microscopy imaging data of …

The promise of single-objective light-sheet microscopy is to combine the convenience of
standard single-objective microscopes with the speed, coverage, resolution and gentleness …

Training stability is of great importance to Transformers. In this work, we investigate the
training dynamics of Transformers by examining the evolution of the attention layers. In …

In recent years, the security of AI systems has drawn increasing research attention,
especially in the medical imaging realm. To develop a secure medical image analysis (MIA) …

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often
required to interpret experimental data. Since nuclear cores dominate electron scattering …

The nuclear shell model is one of the prime many-body methods to study the structure of
atomic nuclei, but it is hampered by an exponential scaling on the basis size as the number …

Quantizing deep neural networks is an effective method for reducing memory consumption
and improving inference speed, and is thus useful for implementation in resource …

Deep Neural Networks (DNNs) are known to be strong predictors, but their prediction
strategies can rarely be understood. With recent advances in Explainable Artificial …

Compared to wheeled vehicles, legged systems have a vast potential to traverse
challenging terrain. To exploit the full potential, it is crucial to tightly integrate terrain …