In Artificial Intelligence (AI) and computational science, learning the mappings between
functions (called operators) defined on complex computational domains is a common …

Characteristics and asymptotics of partial differential equations play an important role in
mathematical physics since they lead to insightful solutions of complex problems that might …

We are concerned with the global weak continuity of the Cartan structural system—or
equivalently, the Gauss–Codazzi–Ricci system—on semi-Riemannian manifolds with lower …

Many domains, including communication, signal processing, and image processing, use the
Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals …

Data-driven smart manufacturing has demonstrated tremendous potential across the entire
manufacturing lifecycle, and initiated and enriched a series of new paradigms, such as …

Molecular simulation is among the most common tools in modern chemistry.
Suchsimulations often suffer from several computational bottlenecks that reducetheir …

Neste trabalho, exploramos as potencialidades do uso da análise de Fourier na detecção e
modelagem de trânsitos planetários de curvas de luz provenientes de FFIs do Telescópio …

In recent years deep learning has produced significant improvements in the field of machine
learning, with some of the greatest successes resulting from the application of convolutional …

Instead of modelling data on regular domains as in classical 1-D or 2-D signal processing,
the field of graph signal processing allows for data to be described and processed on …

Many mechanical problems can be induced from differential equations with boundary
conditions; there exist analytic and numerical methods for solving the differential equations …