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High performance RNNs with spiking neurons
The increasing need for compact and low-power computing solutions for machine learning applications has triggered a renaissance in the study of energy-efficient neural network accelerators.
Mapping high-performance RNNs to in-memory neuromorphic chips
The increasing need for compact and low-power computing solutions for machine learning applications has triggered significant interest in energy-efficient neuromorphic systems.
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