Traffic forecasting is a complex multivariate time-series regression task of paramount
importance for traffic management and planning. However, existing approaches often …

The importance of effective detection is underscored by the fact that socialbots imitate
human behavior to propagate misinformation, leading to an ongoing competition between …

Skin lesion segmentation is a fundamental task in dermoscopic image analysis. The
complex features of pixels in the lesion region impede the lesion segmentation accuracy …

Research on social bot detection plays a crucial role in maintaining the order and reliability
of information dissemination while increasing trust in social interactions. The current …

Recent advancements in social bot detection have been driven by the adoption of Graph
Neural Networks. The social graph, constructed from social network interactions, contains …

Traditional information theory provides a valuable foundation for Reinforcement Learning,
particularly through representation learning and entropy maximization for agent exploration …

Structural Entropy (SE) measures the structural information contained in a graph. Minimizing
or maximizing SE helps to reveal or obscure the intrinsic structural patterns underlying …

Anomalies in graphs involve attributes and structures and may occur at different levels (eg,
node or community). Existing GNN-based detection methods often merely focus on …

We continue studying extremal values of the degree-entropy, which is an information-
theoretic measure defined as the Shannon entropy based on the information functional …

Recently, various methods have been explored to address the challenges of solving the
large-scale flexible Job-shop scheduling problem (FJSP), where operations can be …