December 2024
Intermediate to advanced
494 pages
8h 28m
English
book
Quantum Machine Learning and Optimisation in Finance - Second Edition
by Antoine Jacquier, Oleksiy Kondratyev
Content preview from Quantum Machine Learning and Optimisation in Finance - Second Edition
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Chapter 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 ...
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