Andrew Hallam

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Cancers arise through the progression of multiple genetic and epigenetic defects that lead to deregulation of numerous signalling networks. However, the last decade has seen the development of the concept of 'oncogene addiction', where tumours appear to depend on a single oncogene for survival. RNAi has provided an invaluable tool in the identification of(More)
The goal of this paper is to demonstrate a method for tensorizing neural networks based upon an efficient way of approximating scale invariant quantum states, the Multi-scale Entanglement Renormalization Ansatz (MERA). We employ MERA as a replacement for linear layers in a neural network and test this implementation on the CIFAR-10 dataset. The proposed(More)
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