Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer

no code implementations • 14 Nov 2019 • João Caldeira, Joshua Job, Steven H. Adachi, Brian Nord, Gabriel N. Perdue

We present the application of Restricted Boltzmann Machines (RBMs) to the task of astronomical image classification using a quantum annealer built by D-Wave Systems.

General Classification Image Classification +2

Application of Quantum Annealing to Training of Deep Neural Networks

no code implementations • 21 Oct 2015 • Steven H. Adachi, Maxwell P. Henderson

In Deep Learning, a well-known approach for training a Deep Neural Network starts by training a generative Deep Belief Network model, typically using Contrastive Divergence (CD), then fine-tuning the weights using backpropagation or other discriminative techniques.