DescriptionWe used a quantum annealing D-Wave 2X computer to obtain solutions to NP-hard sparse coding problems for inferring representation of reduced dimensional MNIST images. For comparison, we implemented two deep neural network architectures. The first (AlexNet-like) approximately matched the architecture of the sparse coding model. The second was state-of-the-art (RESNET). Classification based on the D-Wave 2X was superior to matching pursuit and AlexNet and nearly equivalent to RESNET.