
Quantum Machine Learning and Optimisation in Finance
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Persons
Antoine Jacquier graduated from ESSEC Business School before obtaining a PhD in mathematics from Imperial College London. His research focuses on stochastic analysis, asymptotic methods in probability, volatility modelling, and algorithms in quantum computing. He has published about 50 papers and has co-written several books. He is also the director of the MSc in mathematics and finance at Imperial College and regularly works as a quantitative consultant for the finance industry. He has a keen interest in running and whisky.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. Oleksiy is a Visiting Professor at the Department of Mathematics, Imperial College London, and a Research Fellow at ADIA Lab. Outside the world of finance and quantum computing, Oleksiy's passion is for sailing, in particular, offshore racing. Oleksiy holds the RYA Yachtmaster Ocean certificate of competence and is a member of the Royal Ocean Racing Club.
Content
The Principles of Quantum Mechanics
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
Quantum Kernels and Quantum Two-Sample Test
The Power of Parameterised Quantum Circuits
Advanced QML Models
Beyond NISQ
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