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FlatENN: Train Flat for Enhanced Fault Tolerance of Quantized Deep Neural Networks
Moreover, we show that SAQ-trained activation-sparse QDNNs show better accuracy in faulty settings than standard QDNNs trained conventionally.
Exploiting Oxide Based Resistive RAM Variability for Bayesian Neural Network Hardware Design
Uncertainty plays a key role in real-time machine learning.
All-Spin Bayesian Neural Networks
Probabilistic machine learning enabled by the Bayesian formulation has recently gained significant attention in the domain of automated reasoning and decision-making.
Emerging Technologies
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