3 papers
cs.LG2019
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
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…
quant-ph2018
From probabilistic graphical models to generalized tensor networks for supervised learning
Ivan Glasser, Nicola Pancotti, J. Ignacio Cirac
Tensor networks have found a wide use in a variety of applications in physics and computer science, recently leading to both theoretical insights as well as practical algorithms in…