no code implementations • 6 Aug 2019 • Matthias Bal, Hagen Triendl, Mariana Assmann, Michael Craig, Lawrence Phillips, Jarvist Moore Frost, Usman Bashir, Noor Shaker, Vid Stojevic
Architectures for sparse hierarchical representation learning have recently been proposed for graph-structured data, but so far assume the absence of edge features in the graph.
no code implementations • 10 Apr 2018 • Edward Grant, Marcello Benedetti, Shuxiang Cao, Andrew Hallam, Joshua Lockhart, Vid Stojevic, Andrew G. Green, Simone Severini
Quantum circuits with hierarchical structure have been used to perform binary classification of classical data encoded in a quantum state.
Quantum Physics
no code implementations • ICLR 2018 • Andrew Hallam, Edward Grant, Vid Stojevic, Simone Severini, Andrew G. Green
This paper demonstrates a method for tensorizing neural networks based upon an efficient way of approximating scale invariant quantum states, the Multi-scale Entanglement Renormalization Ansatz (MERA).