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@dungscout96
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Adds a tutorial script, tutorial_sus.py, demonstrating how to use EEGDash and Braindecode for contrastive learning on EEG data from a surround suppression task.

Key components:
Contrastive Learning Utilities:

  • Implemented custom ContrastiveSampler and ContrastiveDataset classes to generate and handle pairs of EEG samples for contrastive learning, ensuring correct pairing logic and reproducibility.

Model Architecture and Training:

  • Defined a shallow convolutional encoder (ShallowFBCSPNet) and a classification head, and provided a full training loop using binary cross-entropy loss for the contrastive task, including normalization, optimizer, and scheduler setup. (F
@bruAristimunha
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@dungscout96, the tutorial is not working in the CI, can you please work on this?

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