Advancements in digital automation for smart grids have led to the installation of
measurement devices like phasor measurement units (PMUs), micro-PMUs (-PMUs), and …

The rapid development of information and communications technology has enabled the use
of digital-controlled and software-driven distributed energy resources (DERs) to improve the …

This paper proposes a new method called robust mode connectivity (RMC) to enhance the
adversarial robustness of neural networks (NNs) by exploring a wider range of parameter …

Deep learning models have shown considerable vulnerability to adversarial attacks,
particularly as attacker strategies become more sophisticated. While traditional adversarial …

Convolutional neural networks (CNNs), one of the key architectures of deep learning
models, have achieved superior performance on many machine learning tasks such as …

Currently, power systems are undergoing a rapid energy transition characterized by
significant changes. This transformation encompasses the emergence of smart grids and …

Adversarial robustness is a key concept in measuring the ability of neural networks to
defend against adversarial attacks during the inference phase. Recent studies have shown …

Electric vehicles (EVs) are playing a pivotal role in transportation systems to conform to the
rising exigencies for enhanced performance with safety and hindered environmental impact …