Nengo: a Python tool for building large-scale functional brain models. - Trevor Bekolay; James Bergstra; Eric Hunsberger; Travis DeWolf; Terrence C. Stewart; Daniel Rasmussen; Feng-Xuan Choo; Aaron Voelker; Chris Eliasmith (Frontiers Neuroinformatics, 2013)

Efficient SpiNNaker simulation of a heteroassociative memory using the Neural Engineering Framework. - James C. Knight; Aaron R. Voelker; Andrew Mundy; Chris Eliasmith; Steve B. Furber (IJCNN, 2016)

Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch. - Ken E. Friedl; Aaron R. Voelker; Angelika Peer; Chris Eliasmith (IEEE Robotics Autom. Lett., 2016)

A Spiking Independent Accumulator Model for Winner-Take-All Computation. - Jan Gosmann; Aaron Voelker; Chris Eliasmith (CogSci, 2017)

A Spiking Neural Bayesian Model of Life Span Inference. - Sugandha Sharma; Aaron Voelker; Chris Eliasmith (CogSci, 2017)

A population-level approach to temperature robustness in neuromorphic systems. - Eric Kauderer-Abrams; Andrew Gilbert; Aaron Voelker; Ben Varkey Benjamin; Terrence C. Stewart; Kwabena Boahen 001 (ISCAS, 2017)

Extending the neural engineering framework for nonideal silicon synapses. - Aaron R. Voelker; Ben Varkey Benjamin; Terrence C. Stewart; Kwabena Boahen 001; Chris Eliasmith (ISCAS, 2017)

Methods for applying the Neural Engineering Framework to neuromorphic hardware. - Aaron R. Voelker; Chris Eliasmith (CoRR, 2017)

Point Neurons with Conductance-Based Synapses in the Neural Engineering Framework. - Andreas Stöckel; Aaron R. Voelker; Chris Eliasmith (CoRR, 2017)

Improving With Practice: A Neural Model of Mathematical Development. - Sean Aubin; Aaron R. Voelker; Chris Eliasmith (Top. Cogn. Sci., 2017)

Improving Spiking Dynamical Networks: Accurate Delays, Higher-Order Synapses, and Time Cells. - Aaron R. Voelker; Chris Eliasmith (Neural Comput., 2018)

A neural representation of continuous space using fractional binding. - Brent Komer; Terrence C. Stewart; Aaron Voelker; Chris Eliasmith (CogSci, 2019)

Representing spatial relations with fractional binding. - Thomas Lu; Aaron Voelker; Brent Komer; Chris Eliasmith (CogSci, 2019)

Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks. - Aaron Voelker; Ivana Kajic; Chris Eliasmith (NeurIPS, 2019)

Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model. - Alexander Neckar; Sam Fok; Ben Varkey Benjamin; Terrence C. Stewart; Nick N. Oza; Aaron R. Voelker; Chris Eliasmith; Rajit Manohar; Kwabena Boahen 001 (Proc. IEEE, 2019)

Dynamical Systems in Spiking Neuromorphic Hardware. - Aaron R. Voelker (2019)

A Spike in Performance: Training Hybrid-Spiking Neural Networks with Quantized Activation Functions. - Aaron R. Voelker; Daniel Rasmussen; Chris Eliasmith (CoRR, 2020)

A short letter on the dot product between rotated Fourier transforms. - Aaron R. Voelker (CoRR, 2020)

Hardware Aware Training for Efficient Keyword Spotting on General Purpose and Specialized Hardware. - Peter Blouw; Gurshaant Malik; Benjamin Morcos; Aaron R. Voelker; Chris Eliasmith (CoRR, 2020)

A Neurocomputational Model of Prospective and Retrospective Timing. - Joost de Jong; Aaron R. Voelker; Terrence C. Stewart; Chris Eliasmith; Elkan G. Akyürek; Hedderik van Rijn (CogSci, 2021)

Language Modeling using LMUs: 10x Better Data Efficiency or Improved Scaling Compared to Transformers. - Narsimha Chilkuri; Eric Hunsberger; Aaron Voelker; Gurshaant Malik; Chris Eliasmith (CoRR, 2021)

Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers. - Aaron R. Voelker; Peter Blouw; Xuan Choo; Nicole Sandra-Yaffa Dumont; Terrence C. Stewart; Chris Eliasmith (Neural Comput., 2021)