360 citations · 1.1k across the 14 of their papers we have counts for
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Benchmarking Quantum Hardware for Training of Fully Visible Boltzmann Machines
Dmytro Korenkevych, Yanbo Xue, Zhengbing Bian +4
Quantum annealing (QA) is a hardware-based heuristic optimization and sampling method applicable to discrete undirected graphical models. While similar to simulated annealing, QA r…
Global warming: Temperature estimation in annealers
Jack Raymond, Sheir Yarkoni, Evgeny Andriyash
Sampling from a Boltzmann distribution is NP-hard and so requires heuristic approaches. Quantum annealing is one promising candidate. The failure of annealing dynamics to equilibra…
Quantum Boltzmann Machine
Mohammad H. Amin, Evgeny Andriyash, Jason Rolfe +2
Inspired by the success of Boltzmann Machines based on classical Boltzmann distribution, we propose a new machine learning approach based on quantum Boltzmann distribution of a tra…