research
∙
08/23/2023
LCANets++: Robust Audio Classification using Multi-layer Neural Networks with Lateral Competition
Audio classification aims at recognizing audio signals, including speech...
share
research
∙
07/25/2023
Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor
Neuromorphic processors have garnered considerable interest in recent ye...
research
∙
06/02/2023
Sampling binary sparse coding QUBO models using a spiking neuromorphic processor
We consider the problem of computing a sparse binary representation of a...
research
∙
05/30/2022
Dictionary Learning with Accumulator Neurons
The Locally Competitive Algorithm (LCA) uses local competition between n...
research
∙
12/03/2021
Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer
We present regression and compression algorithms for lattice QCD data ut...
research
∙
06/03/2021
A Little Robustness Goes a Long Way: Leveraging Universal Features for Targeted Transfer Attacks
Adversarial examples for neural network image classifiers are known to b...
research
∙
02/09/2021
Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers
Neural networks trained on visual data are well-known to be vulnerable t...
research
∙
11/23/2020
The Selectivity and Competition of the Mind's Eye in Visual Perception
Research has shown that neurons within the brain are selective to certai...
research
∙
09/03/2020
It's Hard for Neural Networks To Learn the Game of Life
Efforts to improve the learning abilities of neural networks have focuse...
research
∙
11/14/2019
A regression algorithm for accelerated lattice QCD that exploits sparse inference on the D-Wave quantum annealer
We propose a regression algorithm that utilizes a learned dictionary opt...
research
∙
05/28/2019
Image classification using quantum inference on the D-Wave 2X
We use a quantum annealing D-Wave 2X computer to obtain solutions to NP-...
research
∙
11/17/2018
Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples
Although deep learning has shown great success in recent years, research...
research
∙
10/26/2017
Phase Transitions in Image Denoising via Sparsely Coding Convolutional Neural Networks
Neural networks are analogous in many ways to spin glasses, systems whic...
research
∙
05/19/2017
Sparse Coding on Stereo Video for Object Detection
Deep Convolutional Neural Networks (DCNN) require millions of labeled tr...
research
∙
06/17/2014