# Upcoming Seminars

## Sparse Representation based on Dictionary Learning

This work presents the use of the Dictionary Learning method for a sparse representation of 4D seismic data. We consider a trade-off between the number of nonzero coefficients retained in the sparse data representation, the computational cost, and how well we can capture the main features of the original 4D seismic signal. K-SVD is an iterative algorithm used in Dictionary Learning that alternates between the calculation of the sparse representation vector and dictionary update. The algorithm starts with the definition of an initial dictionary (Discrete Cosine Transform, for instance).

## Chasing Water: How ocean currents transport plastic and plankton around the globe

The ocean is in constant motion, with water circulating within and flowing between basins. As the water moves around, it caries heat and nutrients, as well as planktonic organisms and plastic litter around the globe.

The most natural way to study the pathways of water and the connections between ocean basins is using particle trajectories. The trajectories can come from computing of virtual floats in high-resolution ocean models.