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ORCIDAaron Voelker
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2020 – today
- 2021
[j6]Aaron R. Voelker, Peter Blouw, Xuan Choo, Nicole Sandra-Yaffa Dumont
, Terrence C. Stewart, Chris Eliasmith:
Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers. Neural Comput. 33(8): 2033-2067 (2021)- [c10]Joost de Jong, Aaron R. Voelker, Terrence C. Stewart, Chris Eliasmith, Elkan G. Akyürek, Hedderik van Rijn:
A Neurocomputational Model of Prospective and Retrospective Timing. CogSci 2021 - [i6]Narsimha Chilkuri, Eric Hunsberger, Aaron Voelker, Gurshaant Malik, Chris Eliasmith:
Language Modeling using LMUs: 10x Better Data Efficiency or Improved Scaling Compared to Transformers. CoRR abs/2110.02402 (2021) - 2020
- [i5]Aaron R. Voelker, Daniel Rasmussen, Chris Eliasmith:
A Spike in Performance: Training Hybrid-Spiking Neural Networks with Quantized Activation Functions. CoRR abs/2002.03553 (2020) - [i4]Aaron R. Voelker:
A short letter on the dot product between rotated Fourier transforms. CoRR abs/2007.13462 (2020) - [i3]Peter Blouw, Gurshaant Malik, Benjamin Morcos, Aaron R. Voelker, Chris Eliasmith:
Hardware Aware Training for Efficient Keyword Spotting on General Purpose and Specialized Hardware. CoRR abs/2009.04465 (2020)
2010 – 2019
- 2019
- [b1]Aaron R. Voelker:
Dynamical Systems in Spiking Neuromorphic Hardware. University of Waterloo, Ontario, Canada, 2019 - [j5]Alexander Neckar, Sam Fok, Ben Varkey Benjamin, Terrence C. Stewart, Nick N. Oza, Aaron R. Voelker, Chris Eliasmith, Rajit Manohar, Kwabena Boahen:
Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model. Proc. IEEE 107(1): 144-164 (2019) - [c9]Brent Komer, Terrence C. Stewart, Aaron Voelker, Chris Eliasmith:
A neural representation of continuous space using fractional binding. CogSci 2019: 2038-2043 - [c8]Thomas Lu, Aaron Voelker, Brent Komer, Chris Eliasmith:
Representing spatial relations with fractional binding. CogSci 2019: 2214-2220 - [c7]Aaron Voelker, Ivana Kajic, Chris Eliasmith:
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks. NeurIPS 2019: 15544-15553 - 2018
- [j4]Aaron R. Voelker, Chris Eliasmith:
Improving Spiking Dynamical Networks: Accurate Delays, Higher-Order Synapses, and Time Cells. Neural Comput. 30(3) (2018) - 2017
- [j3]Sean Aubin, Aaron R. Voelker, Chris Eliasmith:
Improving With Practice: A Neural Model of Mathematical Development. Top. Cogn. Sci. 9(1): 6-20 (2017) - [c6]Jan Gosmann, Aaron Voelker, Chris Eliasmith:
A Spiking Independent Accumulator Model for Winner-Take-All Computation. CogSci 2017 - [c5]Sugandha Sharma, Aaron Voelker, Chris Eliasmith:
A Spiking Neural Bayesian Model of Life Span Inference. CogSci 2017 - [c4]Eric Kauderer-Abrams, Andrew Gilbert, Aaron Voelker, Ben Varkey Benjamin, Terrence C. Stewart, Kwabena Boahen:
A population-level approach to temperature robustness in neuromorphic systems. ISCAS 2017: 1-4 - [c3]Aaron R. Voelker, Ben Varkey Benjamin, Terrence C. Stewart, Kwabena Boahen, Chris Eliasmith:
Extending the neural engineering framework for nonideal silicon synapses. ISCAS 2017: 1-4 - [i2]Aaron R. Voelker, Chris Eliasmith:
Methods for applying the Neural Engineering Framework to neuromorphic hardware. CoRR abs/1708.08133 (2017) - [i1]Andreas Stöckel, Aaron R. Voelker, Chris Eliasmith:
Point Neurons with Conductance-Based Synapses in the Neural Engineering Framework. CoRR abs/1710.07659 (2017) - 2016
- [j2]Ken E. Friedl, Aaron R. Voelker, Angelika Peer, Chris Eliasmith:
Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch. IEEE Robotics Autom. Lett. 1(1): 516-523 (2016) - [c2]Sean Aubin, Aaron Voelker, Chris Eliasmith:
Improving with Practice: A Neural Model of Mathematical Development. CogSci 2016 - [c1]James C. Knight, Aaron R. Voelker, Andrew Mundy, Chris Eliasmith, Steve B. Furber:
Efficient SpiNNaker simulation of a heteroassociative memory using the Neural Engineering Framework. IJCNN 2016: 5210-5217 - 2013
- [j1]Trevor Bekolay, James Bergstra, Eric Hunsberger, Travis DeWolf, Terrence C. Stewart, Daniel Rasmussen, Feng-Xuan Choo, Aaron Voelker, Chris Eliasmith:
Nengo: a Python tool for building large-scale functional brain models. Frontiers Neuroinformatics 7: 48 (2013)
Coauthor Index
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