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A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealers



Walter Vinci , Lorenzo Buffoni , Hossein Sadeghi , Amir Khoshaman , Evgeny Andriyash , Mohammad H. Amin

* 20 pages, 14 figures 

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PixelVAE++: Improved PixelVAE with Discrete Prior



Hossein Sadeghi , Evgeny Andriyash , Walter Vinci , Lorenzo Buffoni , Mohammad H. Amin


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Learning Undirected Posteriors by Backpropagation through MCMC Updates



Arash Vahdat , Evgeny Andriyash , William G. Macready


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DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors



Arash Vahdat , Evgeny Andriyash , William G. Macready

* Neural Information Processing Systems (NIPS) 2018 

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Improved Gradient-Based Optimization Over Discrete Distributions



Evgeny Andriyash , Arash Vahdat , Bill Macready


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DVAE++: Discrete Variational Autoencoders with Overlapping Transformations



Arash Vahdat , William G. Macready , Zhengbing Bian , Amir Khoshaman , Evgeny Andriyash

* Published as a conference paper at International Conference on Machine Learning (ICML), 2018 

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Quantum Variational Autoencoder



Amir Khoshaman , Walter Vinci , Brandon Denis , Evgeny Andriyash , Mohammad H. Amin

* 12 pages, 3 figures, 2 tables 

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Benchmarking Quantum Hardware for Training of Fully Visible Boltzmann Machines



Dmytro Korenkevych , Yanbo Xue , Zhengbing Bian , Fabian Chudak , William G. Macready , Jason Rolfe , Evgeny Andriyash

* 22 pages, 13 figures, D-Wave quantum system for sampling Boltzmann machines 

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