98 citations · 305 across the 21 of their papers we have counts for
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quant-ph2018★ 9 cited
An Efficient Algorithmic Way to Construct Boltzmann Machine Representations for Arbitrary Stabilizer Code
Yuan-Hang Zhang, Zhian Jia, Yu-Chun Wu +1
Restricted Boltzmann machines (RBMs) have demonstrated considerable success as variational quantum states; however, their representational power remains incompletely understood. In…
quant-ph2018★ 31 cited
Efficient Machine Learning Representations of Surface Code with Boundaries, Defects, Domain Walls and Twists
Zhih-Ahn Jia, Yuan-Hang Zhang, Yu-Chun Wu +3
Machine learning representations of many-body quantum states have recently been introduced as an ansatz to describe the ground states and unitary evolutions of many-body quantum sy…