105 citations · 557 across the 25 of their papers we have counts for
10 papers · 1 filter
Financial Vision Based Differential Privacy Applications
Jun-Hao Chen, Yi-Jen Wang, Yun-Cheng Tsai +1
The importance of deep learning data privacy has gained significant attention in recent years. It is probably to suffer data breaches when applying deep learning to cryptocurrency…
Quantum Architecture Search via Continual Reinforcement Learning
Esther Ye, Samuel Yen-Chi Chen
Quantum computing has promised significant improvement in solving difficult computational tasks over classical computers. Designing quantum circuits for practical use, however, is…
The Dawn of Quantum Natural Language Processing
Riccardo Di Sipio, Jia-Hong Huang, Samuel Yen-Chi Chen +2
In this paper, we discuss the initial attempts at boosting understanding human language based on deep-learning models with quantum computing. We successfully train a quantum-enhanc…
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…
Quantum Architecture Search via Deep Reinforcement Learning
En-Jui Kuo, Yao-Lung L. Fang, Samuel Yen-Chi Chen
Recent advances in quantum computing have drawn considerable attention to building realistic application for and using quantum computers. However, designing a suitable quantum circ…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…
Federated Quantum Machine Learning
Samuel Yen-Chi Chen, Shinjae Yoo
Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially impr…
Quantum machine learning with differential privacy
William M Watkins, Samuel Yen-Chi Chen, Shinjae Yoo
Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. A…
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 Graph Convolutional Network
Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chao Zhang +2
The high energy physics (HEP) community has a long history of dealing with large-scale datasets. To manage such voluminous data, classical machine learning and deep learning techni…