3 citations · 4 across the 6 of their papers we have counts for
6 papers
Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings
Riley Acker, Aman Desai, Garrett Kenyon +1
Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation and represent information thro…
Autonomous Learning of Attractors for Neuromorphic Computing with Wien Bridge Oscillator Networks
Riley Acker, Aman Desai, Garrett Kenyon +1
We present an oscillatory neuromorphic primitive implemented with networks of coupled Wien bridge oscillators and tunable resistive couplings. Phase relationships between oscillato…
Demonstrating the Suitability of Neuromorphic, Event-Based, Dynamic Vision Sensors for In Process Monitoring of Metallic Additive Manufacturing and Welding
David Mascareñas, Andre Green, Ashlee Liao +5
We demonstrate the suitability of high dynamic range, high-speed, neuromorphic event-based, dynamic vision sensors for metallic additive manufacturing and welding for in-process mo…
Comparing Quantum Annealing and Spiking Neuromorphic Computing for Sampling Binary Sparse Coding QUBO Problems
Kyle Henke, Elijah Pelofske, Garrett Kenyon +1
We consider the problem of computing a sparse binary representation of an image. To be precise, given an image and an overcomplete, non-orthonormal basis, we aim to find a sparse b…
Event-to-Video Conversion for Overhead Object Detection
Darryl Hannan, Ragib Arnab, Gavin Parpart +3
Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate down…
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Siddharth Mansingh, Michal Kucer, Garrett Kenyon +2
Deep neural networks (DNNs) are easily fooled by adversarial perturbations that are imperceptible to humans. Adversarial training, a process where adversarial examples are added to…