Extending graph models to incorporate uncertainty is important for many applications, including disease transmission networks, where edges may have a disease transmission probability associated with them, and social networks, where nodes may have an existence probability associated with them. Analysts need tools that support analysis and comparision of these uncertain graphs. To this end, we ha...

Capturing the dependencies among different facial action units (AU) is extremely important for AU detection task. Many studies have employed graph-based deep learning methods to exploit AUs. However, AUs in real world data are often noisy and uncertainty essential be taken into consideration. Rather than employing a deterministic mode, we propose an uncertain graph neural network (UGN) learn pr...

evaluative and comparative analysis among educational projects remains an issue for administration, program directors, instructors, and educational institutes. this study reports a fuzzy complexity model for educational projects, which has two primary aspects (technical aspects and transparency aspects). these aspects may not be measured precisely due to uncertain situations. therefore, a fuzzy...

Large-scale, highly-interconnected networks pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs ar...

In uncertain graphs, the existence of some edges is not predetermined. The diameter of an uncertain graph is essentially an uncertain variable, which indicates the suitability for investigation of its distribution function. The main focus of this paper is to propose an algorithm to determine the distribution function of the diameter of an uncertain graph. We first discuss the characteristics of...

This paper studies the problem of finding the densest subgraph in an uncertain graph. Due to uncertainty in graphs, the traditional definitions of dense subgraphs are not applicable to uncertain graphs. In this paper, we introduce the expected density of an uncertain graph. Based on the expected density, we formalize the problem that, given an uncertain graph G = (V,E, P ) and a set of vertices...

Evaluative and comparative analysis among educational projects remains an issue for administration, program directors, instructors, and educational institutes. This study reports a fuzzy complexity model for educational projects, which has two primary aspects (technical aspects and transparency aspects). These aspects may not be measured precisely due to uncertain situations. Therefore, a fuzzy...