We consider the algorithmic problem of finding the optimal weights and biases for a two-
layer fully connected neural network to fit a given set of data points, also known as empirical …

Graph drawing techniques have been developed in the last few years with the purpose of
producing esthetically pleasing node-link layouts. Recently, the employment of differentiable …

Readability criteria, such as distance or neighborhood preservation, are often used to
optimize node-link representations of graphs to enable the comprehension of the underlying …

By leveraging recent progress of stochastic gradient descent methods, several works have
shown that graphs could be efficiently laid out through the optimization of a tailored objective …

Computational evaluations and benchmarks are widely used for validating graph and
network layout algorithms (aka graph drawing). These evaluations can provide the reader …

Accurate quantification of tumor growth patterns can indicate the development process of the
disease. According to the important features of tumor growth rate and expansion, physicians …

Visual analysis of relational information is vital in most real-life analytics applications.
Automatic layout is a key requirement for effective visual display of such information. This …

Due to their great performance in many challenges, Deep Learning (DL) techniques keep
gaining popularity in many fields. They have been adapted to process graph data structures …

Evaluations—encompassing computational evaluations, benchmarks and user studies—are
essential tools for validating the performance and applicability of graph and network layout …

The normalized stress metric measures how closely distances between vertices in a graph
drawing match the graph-theoretic distances between those vertices. It is one of the most …