10 citations · 11 across the 6 of their papers we have counts for
6 papers
Investigating Quantum-Embedded Transformers on Classical Datasets for Cross-Modality Classification
Hao-Yuan Chen
We test whether a parameterized quantum circuit (PQC) improves a hybrid quantum-classical model's performance on classical datasets, using an interface-matched classical map as the…
Quantum Embedding with Transformer for High-dimensional Data
Hao-Yuan Chen, Yen-Jui Chang, Shih-Wei Liao +1
Quantum embedding with transformers is a novel and promising architecture for quantum machine learning to deliver exceptional capability on near-term devices or simulators. The res…
Hybrid Quantum Neural Network in High-dimensional Data Classification
Hao-Yuan Chen, Yen-Jui Chang, Shih-Wei Liao +1
The research explores the potential of quantum deep learning models to address challenging machine learning problems that classical deep learning models find difficult to tackle. W…
A novel approach for quantum financial simulation and quantum state preparation
Yen-Jui Chang, Wei-Ting Wang, Hao-Yuan Chen +2
Quantum state preparation is vital in quantum computing and information processing. The ability to accurately and reliably prepare specific quantum states is essential for various…
Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems
Hao-Yuan Chen, Yen-Jui Chang, Shih-Wei Liao +1
Quantum computing holds great potential for advancing the limitations of machine learning algorithms to handle higher dimensions of data and reduce overall training parameters in d…
Preparing random state for quantum financing with quantum walks
Yen-Jui Chang, Wei-Ting Wang, Hao-Yuan Chen +2
In recent years, there has been an emerging trend of combining two innovations in computer science and physics to achieve better computation capability. Exploring the potential of…