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Quantum Machine Learning and Optimisation in Finance
book

Quantum Machine Learning and Optimisation in Finance

by Antoine Jacquier, Oleksiy Kondratyev
October 2022
Intermediate to advanced content levelIntermediate to advanced
442 pages
9h 37m
English
Packt Publishing
Content preview from Quantum Machine Learning and Optimisation in Finance

5 Quantum Boltzmann Machine

As we saw in Chapters 3 and 4, quantum annealing can be used to solve hard optimisation problems. However, the range of possible applications of quantum annealing is much wider than that. In this chapter, we will consider two distinct but related use cases that go beyond solving optimisation problems: sampling and training deep neural networks. Specifically, we will focus on the Quantum Boltzmann Machine (QBM) – a generative model that is a direct quantum annealing counterpart of the classical Restricted Boltzmann Machine (RBM), and the Deep Boltzmann Machine (DBM) – a class of deep neural networks composed of multiple layers of latent variables with connections between the layers but not between units within each ...

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Publisher Resources

ISBN: 9781801813570