
Quantum Machine Learning and Optimisation in Finance
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Persons
Antoine Jacquier obtained his PhD in 2010 in Mathematics from Imperial College London, where his research was focused on large deviations and asymptotic methods for stochastic volatility. Over the past 10 years, he has been working on stochastic analysis and volatility modelling, publishing about 50 papers and co-writing several books. He is also the Head of the MSc in Mathematics and Finance at Imperial College and regularly works as a quantitative consultant for the Finance industry.Kondratyev Oleksiy :
Oleksiy Kondratyev obtained his PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine, where his research was focused on studying phase transitions in quantum lattice systems. Oleksiy has over 20 years of quantitative finance experience, primarily in banking. He was recognised as Quant of the Year 2019 by Risk magazine and joined Abu Dhabi Investment Authority as a Quantitative Research & Development Lead in the summer of 2021.
Content
- Adiabatic Quantum Computing
- Quadratic Unconstrained Binary Optimisation
- Quantum Boosting
- Quantum Boltzmann Machine
- Qubits and Quantum Logic Gates
- Parameterised Quantum Circuits and Data Encoding
- Quantum Neural Network
- Quantum Circuit Born Machine
- Variational Quantum Eigensolver
- Quantum Approximate Optimisation Algorithm
- The Power of Parameterised Quantum Circuits
- Looking Ahead
- Bibliography
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The file format ePUB works well for novels and non-fiction books – i.e., 'flowing' text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
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