175 citations · 356 across the 11 of their papers we have counts for
3 papers · 1 filter
Pruning a restricted Boltzmann machine for quantum state reconstruction
Anna Golubeva, Roger G. Melko
Restricted Boltzmann machines (RBMs) have proven to be a powerful tool for learning quantum wavefunction representations from qubit projective measurement data. Since the number of…
The learnability scaling of quantum states: restricted Boltzmann machines
Dan Sehayek, Anna Golubeva, Michael S. Albergo +3
Generative modeling with machine learning has provided a new perspective on the data-driven task of reconstructing quantum states from a set of qubit measurements. As increasingly…
QuCumber: wavefunction reconstruction with neural networks
Matthew J. S. Beach, Isaac De Vlugt, Anna Golubeva +6
As we enter a new era of quantum technology, it is increasingly important to develop methods to aid in the accurate preparation of quantum states for a variety of materials, matter…