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Found 4 papers, 1 papers with code
Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks
In STDBP algorithm, the timing of individual spikes is used to convey information (temporal coding), and learning (back-propagation) is performed based on spike timing in an event-driven manner.
You Only Spike Once: Improving Energy-Efficient Neuromorphic Inference to ANN-Level Accuracy
Rate-encoded SNNs could be seen as inefficient as an encoding scheme because it involves the transmission of a large number of spikes.
SOTERIA: In Search of Efficient Neural Networks for Private Inference
In this setting, our objective is to protect the confidentiality of both the users' input queries as well as the model parameters at the server, with modest computation and communication overhead.
Multiply-and-Fire (MNF): An Event-driven Sparse Neural Network Accelerator
Machine learning, particularly deep neural network inference, has become a vital workload for many computing systems, from data centers and HPC systems to edge-based computing.
