516 citations · 4.2k across the 120 of their papers we have counts for
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Compact Neural Networks based on the Multiscale Entanglement Renormalization Ansatz
Andrew Hallam, Edward Grant, Vid Stojevic +2
This paper demonstrates a method for tensorizing neural networks based upon an efficient way of approximating scale invariant quantum states, the Multi-scale Entanglement Renormali…
Learning hard quantum distributions with variational autoencoders
Andrea Rocchetto, Edward Grant, Sergii Strelchuk +2
Studying general quantum many-body systems is one of the major challenges in modern physics because it requires an amount of computational resources that scales exponentially with…
How to Suppress Dark States in Quantum Networks and Bio-Engineered Structures
T. P. Le, Ludovica Donati, Simone Severini +1
Transport across quantum networks underlies many problems, from state transfer on a spin network to energy transport in photosynthetic complexes. However, networks can contain dark…
Quantum machine learning: a classical perspective
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo +4
Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classifica…
Weak Modular Product of Bipartite Graphs, Bicliques and Isomorphism
Danial Dervovic, Simone Severini
A 1978 theorem of Kozen states that two graphs on vertices are isomorphic if and only if there is a clique of size in the weak modular product between the two graphs. Restr…
Entanglement properties of quantum grid states
Joshua Lockhart, Otfried Gühne, Simone Severini
Grid states form a discrete set of mixed quantum states that can be described by graphs. We characterize the entanglement properties of these states and provide methods to evaluate…