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06/17/2022
Debugging using Orthogonal Gradient Descent
In this report we consider the following problem: Given a trained model ...
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10/05/2021
Language Modeling using LMUs: 10x Better Data Efficiency or Improved Scaling Compared to Transformers
Recent studies have demonstrated that the performance of transformers on...
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06/16/2021
A Spiking Neural Network for Image Segmentation
We seek to investigate the scalability of neuromorphic computing for com...
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02/22/2021
Parallelizing Legendre Memory Unit Training
Recently, a new recurrent neural network (RNN) named the Legendre Memory...
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09/18/2020
Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi
We implemented two neural network based benchmark tasks on a prototype c...
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09/09/2020
Hardware Aware Training for Efficient Keyword Spotting on General Purpose and Specialized Hardware
Keyword spotting (KWS) provides a critical user interface for many mobil...
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07/20/2020
Nengo and low-power AI hardware for robust, embedded neurorobotics
In this paper we demonstrate how the Nengo neural modeling and simulatio...
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02/10/2020
A Spike in Performance: Training Hybrid-Spiking Neural Networks with Quantized Activation Functions
The machine learning community has become increasingly interested in the...
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04/26/2019
Passive nonlinear dendritic interactions as a general computational resource in functional spiking neural networks
Nonlinear interactions in the dendritic tree play a key role in neural c...
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12/04/2018
Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware
Using Intel's Loihi neuromorphic research chip and ABR's Nengo Deep Lear...
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10/20/2017
Point Neurons with Conductance-Based Synapses in the Neural Engineering Framework
The mathematical model underlying the Neural Engineering Framework (NEF)...
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08/27/2017
Methods for applying the Neural Engineering Framework to neuromorphic hardware
We review our current software tools and theoretical methods for applyin...
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11/16/2016
Training Spiking Deep Networks for Neuromorphic Hardware
We describe a method to train spiking deep networks that can be run usin...
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02/16/2016
BioSpaun: A large-scale behaving brain model with complex neurons
We describe a large-scale functional brain model that includes detailed,...
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10/29/2015