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

Recipe for SEMpy library

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

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).

This project contains gazebo simulations environment for use with ros2.

Forked from https://github.com/arkworks-rs/poly-commit. Required as a dependency by https://gitlab.isae-supaero.fr/dragoon/pcs-fec-id.