activity
20162026
most citedTraining Spiking Deep Networks for Neuromorphic Hardware

109 citations · 157 across the 6 of their papers we have counts for

collaborators

15 papers

cs.RO2026

A Spiking Neural Architecture for Coordinating Arm and Locomotor Control

Lea Steffen, Kathryn Simone, Graeme Damberger +3

Spiking Neural Networks (SNNs) coupled with neuromorphic hardware offer energy-efficient solutions for humanoid robot control. However, existing SNN-based motor control systems add…

cs.LG2022★ 1 cited

Debugging using Orthogonal Gradient Descent

Narsimha Chilkuri, Chris Eliasmith

In this report we consider the following problem: Given a trained model that is partially faulty, can we correct its behaviour without having to train the model from scratch? In ot…

cs.LG2021★ 5 cited

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.…

cs.NE2021★ 37 cited

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…

cs.LG2021

Parallelizing Legendre Memory Unit Training

Narsimha Chilkuri, Chris Eliasmith

Recently, a new recurrent neural network (RNN) named the Legendre Memory Unit (LMU) was proposed and shown to achieve state-of-the-art performance on several benchmark datasets. He…

cs.NE2020

Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi

Yexin Yan, Terrence C. Stewart, Xuan Choo +7

We implemented two neural network based benchmark tasks on a prototype chip of the second-generation SpiNNaker (SpiNNaker 2) neuromorphic system: keyword spotting and adaptive robo…