We present a review of the state of the art of segmentation and partitioning techniques of
boundary meshes. Recently, these have become a part of many mesh and object …

In this work we show that the flexibility of the discontinuous Galerkin (dG) discretization can
be fruitfully exploited to implement numerical solution strategies based on the use of …

Many important graph applications are iterative algorithms that repeatedly process the input
graph until convergence. For such algorithms, graph abstraction is an important technique …

This paper presents the first classical Convolutional Neural Network (CNN) that can be
applied directly to data from unstructured finite element meshes or control volume grids …

We present a formulation of boundary mesh segmentation as an optimization problem.
Previous segmentation solutions are classified according to the different segmentation …

For unstructured finite volume methods an agglomeration multigrid with an implicit
multistage Runge–Kutta method as a smoother is developed for solving the compressible …

In this report we present the state of the art on segmentation, or partitioning techniques used
on boundary meshes. Recently, these have become a part of many mesh and object …

In this paper we analyze the convergence properties of two-level and W-cycle multigrid
solvers for the numerical solution of the linear system of equations arising from hp-version …

Large-scale parallel graph analytics involves executing iterative algorithms (eg, PageRank,
Shortest Paths, etc.) that are both data-and compute-intensive. In this work we construct …

This paper presents the first classical Convolutional Neural Network (CNN) that can be
applied directly to data from unstructured finite element meshes or control volume grids …