46 citations · 98 across the 12 of their papers we have counts for
3 papers · 1 filter
SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks
Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang +3
SNNs are an active research domain towards energy efficient machine intelligence. Compared to conventional ANNs, SNNs use temporal spike data and bio-plausible neuronal activation…
Efficient Network Construction through Structural Plasticity
Xiaocong Du, Zheng Li, Yufei Ma +1
Deep Neural Networks (DNNs) on hardware is facing excessive computation cost due to the massive number of parameters. A typical training pipeline to mitigate over-parameterization…
Algorithm and Hardware Design of Discrete-Time Spiking Neural Networks Based on Back Propagation with Binary Activations
Shihui Yin, Shreyas K. Venkataramanaiah, Gregory K. Chen +4
We present a new back propagation based training algorithm for discrete-time spiking neural networks (SNN). Inspired by recent deep learning algorithms on binarized neural networks…