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Quantum-Inspired Tensor Neural Networks for Option Pricing
Recent advances in deep learning have enabled us to address the curse of dimensionality (COD) by solving problems in higher dimensions.
Quantum-Inspired Tensor Neural Networks for Partial Differential Equations
We demonstrate that TNN provide significant parameter savings while attaining the same accuracy as compared to the classical Dense Neural Network (DNN).
Variational Quantum Reinforcement Learning via Evolutionary Optimization
Recent advance in classical reinforcement learning (RL) and quantum computation (QC) points to a promising direction of performing RL on a quantum computer.
An end-to-end trainable hybrid classical-quantum classifier
We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks.
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit
One key step in performing quantum machine learning (QML) on noisy intermediate-scale quantum (NISQ) devices is the dimension reduction of the input data prior to their encoding.
