105 citations · 217 across the 6 of their papers we have counts for
6 papers
Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels
Chia-Wei Hsing, Wei-Lin Tu
Convolutional Neural Networks (CNNs) excel at extracting local features hierarchically, but their performance in capturing complex correlations hinges heavily on deep architectures…
Quantum-Inspired Tensor Neural Networks for Option Pricing
Raj G. Patel, Chia-Wei Hsing, Serkan Sahin +12
Recent advances in deep learning have enabled us to address the curse of dimensionality (COD) by solving problems in higher dimensions. A subset of such approaches of addressing th…
Quantum-Inspired Tensor Neural Networks for Partial Differential Equations
Raj Patel, Chia-Wei Hsing, Serkan Sahin +11
Partial Differential Equations (PDEs) are used to model a variety of dynamical systems in science and engineering. Recent advances in deep learning have enabled us to solve them in…
Variational Quantum Reinforcement Learning via Evolutionary Optimization
Samuel Yen-Chi Chen, Chih-Min Huang, Chia-Wei Hsing +2
Recent advance in classical reinforcement learning (RL) and quantum computation (QC) points to a promising direction of performing RL on a quantum computer. However, potential appl…
An end-to-end trainable hybrid classical-quantum classifier
Samuel Yen-Chi Chen, Chih-Min Huang, Chia-Wei Hsing +1
We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks. This architecture allows for the cla…
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit
Samuel Yen-Chi Chen, Chih-Min Huang, Chia-Wei Hsing +1
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. T…