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Deep neural networks have achieved impressive performance in many applications but their large number of parameters lead to significant computational and storage overheads.
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A guide to deep learning in healthcare
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Experimental security research of tesla autopilot
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Random mask: Towards robust convolutional neural networks, 2019
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Theoretically principled trade-off between robustness and accuracy
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