213 citations · 496 across the 9 of their papers we have counts for
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cs.LG2019★ 23 cited
Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
Ivan Glasser, Ryan Sweke, Nicola Pancotti +2
Tensor-network techniques have enjoyed outstanding success in physics, and have recently attracted attention in machine learning, both as a tool for the formulation of new learning…
quant-ph2019★ 121 cited
NetKet: A Machine Learning Toolkit for Many-Body Quantum Systems
Giuseppe Carleo, Kenny Choo, Damian Hofmann +15
We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and…