We build on the recently introduced PDE-G-CNN framework, which proposed the concept of
non-linear morphological convolutions that are motivated by solving HJB-PDEs on lifted …

Euclidean deep learning is often inadequate for addressing real-world signals where the
representation space is irregular and curved with complex topologies. Interpreting the …

The field of machine learning is currently undergoing rapid development, with applications
in various areas, including image processing. In particular, Convolutional Neural Networks …