105 citations · 557 across the 25 of their papers we have counts for
6 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…
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…
Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chao Zhang +2
This work presents a quantum convolutional neural network (QCNN) for the classification of high energy physics events. The proposed model is tested using a simulated dataset from t…
Data Augmentation for Deep Candlestick Learner
Chia-Ying Tsao, Jun-Hao Chen, Samuel Yen-Chi Chen +1
To successfully build a deep learning model, it will need a large amount of labeled data. However, labeled data are hard to collect in many use cases. To tackle this problem, a bun…
Explainable Deep Convolutional Candlestick Learner
Jun-Hao Chen, Samuel Yen-Chi Chen, Yun-Cheng Tsai +1
Candlesticks are graphical representations of price movements for a given period. The traders can discovery the trend of the asset by looking at the candlestick patterns. Although…
Variational Quantum Circuits for Deep Reinforcement Learning
Samuel Yen-Chi Chen, Chao-Han Huck Yang, Jun Qi +3
The state-of-the-art machine learning approaches are based on classical von Neumann computing architectures and have been widely used in many industrial and academic domains. With…