212 citations · 363 across the 4 of their papers we have counts for
5 papers
Language Modeling using LMUs: 10x Better Data Efficiency or Improved Scaling Compared to Transformers
Narsimha Chilkuri, Eric Hunsberger, Aaron Voelker +2
Recent studies have demonstrated that the performance of transformers on the task of language modeling obeys a power-law relationship with model size over six orders of magnitude.…
A Spiking Neural Network for Image Segmentation
Kinjal Patel, Eric Hunsberger, Sean Batir +1
We seek to investigate the scalability of neuromorphic computing for computer vision, with the objective of replicating non-neuromorphic performance on computer vision tasks while…
Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware
Peter Blouw, Xuan Choo, Eric Hunsberger +1
Using Intel's Loihi neuromorphic research chip and ABR's Nengo Deep Learning toolkit, we analyze the inference speed, dynamic power consumption, and energy cost per inference of a…
Training Spiking Deep Networks for Neuromorphic Hardware
Eric Hunsberger, Chris Eliasmith
We describe a method to train spiking deep networks that can be run using leaky integrate-and-fire (LIF) neurons, achieving state-of-the-art results for spiking LIF networks on fiv…
Spiking Deep Networks with LIF Neurons
Eric Hunsberger, Chris Eliasmith
We train spiking deep networks using leaky integrate-and-fire (LIF) neurons, and achieve state-of-the-art results for spiking networks on the CIFAR-10 and MNIST datasets. This demo…