Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

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Catastrophic overfitting (CO) in single-step adversarial training (AT) results in abrupt drops in the adversarial test accuracy (even down to 0%). For models trained with multi-step AT, it has been observed that the loss function behaves locally linearly w ...

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Chattez avec Graph Search

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Sparse autoregressive neural networks for classical spin systems

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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