<span class="var-sub_title">Comparing Deep Learning with Quantum Inference on The D-Wave 2X</span> SC18 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

The 3rd International Workshop on Post-Moore Era Supercomputing (PMES)


Comparing Deep Learning with Quantum Inference on The D-Wave 2X

Abstract: We 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.

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