Active learning is a decision-making process. In both abstract and physical settings, active
learning demands both analysis and action. This is a review of active learning in robotics …

This paper provides a theoretical background for Lagrangian Descriptors (LDs). The goal of
achieving rigorous proofs that justify the ability of LDs to detect invariant manifolds is …

The chaotic nature of ocean motion is a major challenge that hinders the discovery of spatio-
temporal current routes that govern the transport of material. Certain material, such as oil …

Abstract Transoceanic Gliders are Autonomous Underwater Vehicles (AUVs) for which there
is a developing and expanding range of applications in open-seas research, technology and …

Mesoscale eddies are one of the most prominent processes in the world's ocean. The eddy-
induced transport of water mass, heat, and energy has a great impact on the ocean and …

This paper proposes a new uncertainty measure, appropriate for quantifying the
performance of transport models in assessing the origin or source of a given observation. It …

This paper discusses the combined use of tools from dynamical systems theory and remote
sensing techniques and shows how they are effective instruments which may greatly …

Phase space structures such as dividing surfaces, normally hyperbolic invariant manifolds,
and their stable and unstable manifolds have been an integral part of computing quantitative …

We present a method based on a Lagrangian descriptor for revealing the high-dimensional
phase space structures that are of interest in nonlinear Hamiltonian systems with index-1 …

The Maslov index of a periodic orbit is an important piece in the semiclassical quantization
of nonintegrable systems, while almost all existing techniques that lead to a rigorous …