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What Variables Affect Out-Of-Distribution Generalization in Pretrained Models?
Embeddings produced by pre-trained deep neural networks (DNNs) are widely used; however, their efficacy for downstream tasks can vary widely.
Sleep-Like Unsupervised Replay Improves Performance when Data are Limited or Unbalanced
This study sheds light on a potential synaptic weight dynamics strategy employed by the brain during sleep to enhance memory performance when training data are limited or imbalanced.
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks
In this work, we utilize a biologically inspired sleep phase in ANNs and demonstrate the benefit of sleep on defending against adversarial attacks as well as in increasing ANN classification robustness.
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