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NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems



Filippo Vicentini , Damian Hofmann , Attila Szabó , Dian Wu , Christopher Roth , Clemens Giuliani , Gabriel Pescia , Jannes Nys , Vladimir Vargas-Calderon , Nikita Astrakhantsev , Giuseppe Carleo

* 55 pages, 5 figures. Accompanying code at https://github.com/netket/netket 

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Continuous-variable neural-network quantum states and the quantum rotor model



James Stokes , Saibal De , Shravan Veerapaneni , Giuseppe Carleo


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Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks



Dian Wu , Riccardo Rossi , Giuseppe Carleo

* 8 pages, 5 figures 

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Neural tensor contractions and the expressive power of deep neural quantum states



Or Sharir , Amnon Shashua , Giuseppe Carleo


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Gauge equivariant neural networks for quantum lattice gauge theories



Di Luo , Giuseppe Carleo , Bryan K. Clark , James Stokes


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Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states



James Stokes , Javier Robledo Moreno , Eftychios A. Pnevmatikakis , Giuseppe Carleo


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Natural evolution strategies and quantum approximate optimization



Tianchen Zhao , Giuseppe Carleo , James Stokes , Shravan Veerapaneni


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Quantum Natural Gradient



James Stokes , Josh Izaac , Nathan Killoran , Giuseppe Carleo

* 9 pages, 2 figures 

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Deep autoregressive models for the efficient variational simulation of many-body quantum systems



Or Sharir , Yoav Levine , Noam Wies , Giuseppe Carleo , Amnon Shashua


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Learning hard quantum distributions with variational autoencoders



Andrea Rocchetto , Edward Grant , Sergii Strelchuk , Giuseppe Carleo , Simone Severini

* npj Quantum Information, Volume 4, Article number: 28 (2018) 
* v2: 9 pages, 3 figures, journal version with major edits with respect to v1 (rewriting of section "hard and easy quantum states", extended discussion on comparison with tensor networks) 

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