1 citations · 2 across the 3 of their papers we have counts for
4 papers
Activation-Energy Pruning for Spiking Neural Networks: Unsupervised Personalization via Spike-Count Saliency
Joseph Bingham
Activation-energy pruning -- removing weights whose product of magnitude and cumulative pre-synaptic spike count falls below a threshold -- was established as an effective unsuperv…
Bonsai: A Framework for Convolutional Neural Network Acceleration Using Criterion-Based Pruning
Joseph Bingham, Sam Helmich
As the need for more accurate and powerful Convolutional Neural Networks (CNNs) increases, so too does the size, execution time, memory footprint, and power consumption. To overcom…
Fine-Pruning: A Biologically Inspired Algorithm for Personalization of Machine Learning Models
Joseph Bingham, Saman Zonouz, Dvir Aran
Neural networks have long strived to emulate the learning capabilities of the human brain. While deep neural networks (DNNs) draw inspiration from the brain in neuron design, their…
Guide-Guard: Off-Target Predicting in CRISPR Applications
Joseph Bingham, Netanel Arussy, Saman Zonouz
With the introduction of cyber-physical genome sequencing and editing technologies, such as CRISPR, researchers can more easily access tools to investigate and create remedies for…