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This project contains gazebo simulations environment for use with ros2.

A deep learning auto-regressive method is trained to learn the acoustic propagation in presence of obstacles. The method is flexible to account for both far-fields prediction (non-reflecting cases) as well as duct acoustics (non-reflecting BCs).

Recipe for SEMpy library

Reproducibility study of a multiscale CNN used for modelling PDE's

Effects of Boundary Conditions in Fully Convolutional Networks for Learning Spatio-temporal Dynamics