Reliable and efficient trajectory generation methods are a fundamental need for
autonomous dynamical systems. The goal of this article is to provide a comprehensive …

Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

Optimization on Riemannian manifolds-the result of smooth geometry and optimization
merging into one elegant modern framework-spans many areas of science and engineering …

SciPy is an open-source scientific computing library for the Python programming language.
Since its initial release in 2001, SciPy has become a de facto standard for leveraging …

Transfer learning has fundamentally changed the landscape of natural language processing
(NLP) research. Many existing state-of-the-art models are first pre-trained on a large text …

This paper studies the unmanned aerial vehicle (UAV)-enabled integrated sensing and
communication (ISAC), in which UAVs are dispatched as aerial dual-functional access …

In many optimization problems arising from scientific, engineering and artificial intelligence
applications, objective and constraint functions are available only as the output of a black …

Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …

We propose a method for annotating images of a hand manipulating an object with the 3D
poses of both the hand and the object, together with a dataset created using this method …

Incorporating second-order curvature information into machine learning optimization
algorithms can be subtle, and doing so naïvely can lead to high per-iteration costs …