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Attention Augmented Convolutional Networks

Final project of KTH course DD2424 Deep Learning in Data Science. This project consists of a simplified replication of the paper Attention Augmented Convolutional Networks. The main goal was augmenting Convolutional Networks by means of self-attention. As a result, we have convolutions that also detect long range interactions.

To run the experiments:

  • Go to scripts.
  • Select the architecture of the network.
  • Modify the network parameters to customize the architecture.
  • Run the selected code (it needs TensorFlow in its version 2 to run).

The conclsusions of the different experiments can be found in Group76 Project Report.