360 citations · 1.1k across the 14 of their papers we have counts for
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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…
Quantum Variational Autoencoder
Amir Khoshaman, Walter Vinci, Brandon Denis +3
Variational autoencoders (VAEs) are powerful generative models with the salient ability to perform inference. Here, we introduce a quantum variational autoencoder (QVAE): a VAE who…