Utilization of small molecules as passivation materials for perovskite solar cells (PSCs) has gained significant attention recently, with hundreds of small molecules demonstrating passivation effects. In this study, a high-accuracy machine learning model i ...
Molecular junctions represent a fascinating frontier in the realm of nanotechnology and are one of the
smallest optoelectronic devices possible, consisting of individual molecules or a group of molecules
that serve as the active element sandwiched between ...
Quantum optics studies how photons interact with other forms of matter, the understanding of which was crucial for the development of quantum mechanics as a whole. Starting from the photoelectric effect, the quantum property of light has led to the develop ...
In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...
This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...
The spatial distribution of dwarf galaxies around their host galaxies is a critical test for the standard model of cosmology because it probes the dynamics of dark matter halos and is independent of the internal baryonic processes of galaxies. Comoving pla ...
We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...
We report the discovery of 15 exceptionally luminous 10 less than or similar to z less than or similar to 14 candidate galaxies discovered in the first 0.28 deg(2) of JWST/NIRCam imaging from the COSMOS-Web survey. These sources span rest-frame UV magnitud ...
In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches have shown remarkable success on synthetic datasets, we have observed them to fail in the presence of real-world data. We ...
We demonstrate the importance of addressing the F vertex and thus going beyond the GW approximation for achieving the energy levels of liquid water in manybody perturbation theory. In particular, we consider an effective vertex function in both the polariz ...