A Hybrid Quantum enabled RBM Advantage: Convolutional Autoencoders For Quantum Image Compression and Generative Learning

31 January 2020

Papers citing "A Hybrid Quantum enabled RBM Advantage: Convolutional Autoencoders For Quantum Image Compression and Generative Learning"

7 / 7 papers shown

Title
A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealers Walter Winci L. Buffoni Hossein Sadeghi Amir Khoshaman Evgeny Andriyash Mohammad H. Amin BDL DRL 45 59 0 04 Dec 2019
Quantum Variational Autoencoder Amir Khoshaman W. Vinci Brandon Denis Evgeny Andriyash Hossein Sadeghi Mohammad H. Amin BDL DRL 49 177 0 15 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,883 0 25 Aug 2017
Nonnegative/binary matrix factorization with a D-Wave quantum annealer Daniel O’Malley V. Vesselinov Boian S. Alexandrov L. Alexandrov 43 107 0 05 Apr 2017
Deep Restricted Boltzmann Networks Hengyuan Hu Lisheng Gao Quanbin Ma BDL AI4CE 40 15 0 15 Nov 2016
Application of Quantum Annealing to Training of Deep Neural Networks S. Adachi Maxwell P. Henderson BDL 52 239 0 21 Oct 2015
On the Challenges of Physical Implementations of RBMs Vincent Dumoulin Ian Goodfellow Aaron Courville Yoshua Bengio AI4CE 69 60 0 18 Dec 2013