30 citations · 94 across the 20 of their papers we have counts for
22 papers
Sampling binary sparse coding QUBO models using a spiking neuromorphic processor
Kyle Henke, Elijah Pelofske, Georg Hahn +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…
LCANets++: Robust Audio Classification using Multi-layer Neural Networks with Lateral Competition
Sayanton V. Dibbo, Juston S. Moore, Garrett T. Kenyon +1
Audio classification aims at recognizing audio signals, including speech commands or sound events. However, current audio classifiers are susceptible to perturbations and adversari…
Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor
Gavin Parpart, Sumedh R. Risbud, Garrett T. Kenyon +1
Neuromorphic processors have garnered considerable interest in recent years for their potential in energy-efficient and high-speed computing. The Locally Competitive Algorithm (LCA…
Dictionary Learning with Accumulator Neurons
Gavin Parpart, Carlos Gonzalez, Terrence C. Stewart +6
The Locally Competitive Algorithm (LCA) uses local competition between non-spiking leaky integrator neurons to infer sparse representations, allowing for potentially real-time exec…
On visual self-supervision and its effect on model robustness
Michal Kucer, Diane Oyen, Garrett Kenyon
Recent self-supervision methods have found success in learning feature representations that could rival ones from full supervision, and have been shown to be beneficial to the mode…
Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer
Boram Yoon, Chia Cheng Chang, Garrett T. Kenyon +2
We present regression and compression algorithms for lattice QCD data utilizing the efficient binary optimization ability of quantum annealers. In the regression algorithm, we enco…