Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

Self-supervised representation learning methods have achieved significant success in
computer vision and natural language processing (NLP), where data samples exhibit explicit …

With the advancement of computer technology, transformer models have been applied to the
field of computer vision (CV) after their success in natural language processing (NLP). In …

The use of centralized training and decentralized execution for value function factorization
demonstrates the potential for addressing cooperative multi-agent reinforcement tasks …

Textual backdoor attacks pose significant security threats. Current detection approaches,
typically relying on intermediate feature representation or reconstructing potential triggers …

To develop the most appropriate control strategy and monitor, maintain, and evaluate the
traffic performance of the freeway weaving areas, state and local Departments of …

Trustworthy process monitoring seeks to build an accurate and interpretable monitoring
framework, which is critical for ensuring the safety of energy conversion plant (ECP) that …

A smart grid is a new type of power system based on modern information technology, which
utilises advanced communication, computing and control technologies and employs …

Accurate prediction of energy consumption is pivotal to achieving sustainable building
energy objectives, and Deep Reinforcement Learning (DRL) has demonstrated efficacy in …

In this study, we introduce SAVAGE, a novel framework for sparse vicious adversarial link
prediction attacks in graph neural networks (GNNs). While GNNs have been successful in …