Quantum Machine Learning for Finance

Abstract

Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and long terms, but even in the short term. This review paper presents the state of the art of quantum algorithms for financial applications, with particular focus to those use cases that can be solved via Machine Learning.

References in corpus (23)

• Generative Adversarial Networks
• Quantum algorithm for solving linear systems of equations
• The power of quantum neural networks
• Quantum random access memory
• The effect of data encoding on the expressive power of variational quantum machine learning models
• Power of data in quantum machine learning
• Quantum Data Fitting
• Quantum reinforcement learning
• Creating superpositions that correspond to efficiently integrable probability distributions
• Supervised quantum machine learning models are kernel methods
• Towards understanding the power of quantum kernels in the NISQ era
• Quantum K-nearest neighbor classification algorithm based on Hamming distance
• Quantum Algorithms for Compositional Natural Language Processing
• Learning temporal data with variational quantum recurrent neural network
• Anomaly detection with variational quantum generative adversarial networks
• A Domain-agnostic, Noise-resistant, Hardware-efficient Evolutionary Variational Quantum Eigensolver
• The Efficient Preparation of Normal Distributions in Quantum Registers
• Sublinear quantum algorithms for training linear and kernel-based classifiers
• K-Means Clustering on Noisy Intermediate Scale Quantum Computers
• Quantum Long Short-Term Memory
• Quantum Algorithms for Reinforcement Learning with a Generative Model
• Application of deep quantum neural networks to finance
• Quantum-Assisted Clustering Algorithms for NISQ-Era Devices

Cited by in corpus (8)

• Quantum computing for finance
• Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer
• Quantum version of the k-NN classifier based on a quantum sorting algorithm
• Expressivity of Variational Quantum Machine Learning on the Boolean Cube
• QRAM: A Survey and Critique
• Approaching Collateral Optimization for NISQ and Quantum-Inspired Computing
• Contextual Quantum Neural Networks for Stock Price Prediction
• Evaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing