We survey foundational features underlying modern graph query languages. We first
discuss two popular graph data models: edge-labelled graphs, where nodes are connected …

Simultaneous localization and map** (SLAM) in unknown GPS‐denied environments is a
major challenge for researchers in the field of mobile robotics. Many solutions for single …

Many underlying relationships among data in several areas of science and engineering, eg,
computer vision, molecular chemistry, molecular biology, pattern recognition, and data …

Graph matching (GM) is a fundamental problem in computer science, and it plays a central
role to solve correspondence problems in computer vision. GM problems that incorporate …

In this paper we survey methods for performing a comparative graph analysis and explain
the history, foundations and differences of such techniques of the last 50 years. While …

Graph matching, which refers to a class of computational problems of finding an optimal
correspondence between the vertices of graphs to minimize (maximize) their node and edge …

The notions of distance and similarity play a key role in many machine learning approaches,
and artificial intelligence in general, since they can serve as an organizing principle by …

Chronic Fatigue Syndrome (CFS) is a complex illness affecting 4 million Americans for
which no characteristic lesion has been identified. Instead of searching for a deficiency in …

Graph neural networks (GNNs) are effective machine learning models for many graph-
related applications. Despite their empirical success, many research efforts focus on the …

Because the properties of objects are largely determined by their geometric features, shape
analysis and classification are essential to almost every applied scientific and technological …