360 citations · 1.1k across the 14 of their papers we have counts for
14 papers
A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealers
Walter Vinci, Lorenzo Buffoni, Hossein Sadeghi +3
The development of quantum-classical hybrid (QCH) algorithms is critical to achieve state-of-the-art computational models. A QCH variational autoencoder (QVAE) was introduced in Re…
PixelVAE++: Improved PixelVAE with Discrete Prior
Hossein Sadeghi, Evgeny Andriyash, Walter Vinci +2
Constructing powerful generative models for natural images is a challenging task. PixelCNN models capture details and local information in images very well but have limited recepti…
Undirected Graphical Models as Approximate Posteriors
Arash Vahdat, Evgeny Andriyash, William G. Macready
The representation of the approximate posterior is a critical aspect of effective variational autoencoders (VAEs). Poor choices for the approximate posterior have a detrimental imp…
Improved Gradient-Based Optimization Over Discrete Distributions
Evgeny Andriyash, Arash Vahdat, Bill Macready
In many applications we seek to maximize an expectation with respect to a distribution over discrete variables. Estimating gradients of such objectives with respect to the distribu…
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors
Arash Vahdat, Evgeny Andriyash, William G. Macready
Boltzmann machines are powerful distributions that have been shown to be an effective prior over binary latent variables in variational autoencoders (VAEs). However, previous metho…
Observation of topological phenomena in a programmable lattice of 1,800 qubits
Andrew D. King, Juan Carrasquilla, Isil Ozfidan +20
The celebrated work of Berezinskii, Kosterlitz and Thouless in the 1970s revealed exotic phases of matter governed by topological properties of low-dimensional materials such as th…