105 citations · 557 across the 25 of their papers we have counts for
27 papers
A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity
Ryan L'Abbate, Anthony D'Onofrio, Samuel Stein +5
Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constrain…
Quantum deep Q learning with distributed prioritized experience replay
Samuel Yen-Chi Chen
This paper introduces the QDQN-DPER framework to enhance the efficiency of quantum reinforcement learning (QRL) in solving sequential decision tasks. The framework incorporates pri…
Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction
Daniel Fry, Amol Deshmukh, Samuel Yen-Chi Chen +2
Quantum reservoir computing is strongly emerging for sequential and time series data prediction in quantum machine learning. We make advancements to the quantum noise-induced reser…
Reservoir Computing via Quantum Recurrent Neural Networks
Samuel Yen-Chi Chen, Daniel Fry, Amol Deshmukh +2
Recent developments in quantum computing and machine learning have propelled the interdisciplinary study of quantum machine learning. Sequential modeling is an important task with…
Quantum deep recurrent reinforcement learning
Samuel Yen-Chi Chen
Recent advances in quantum computing (QC) and machine learning (ML) have drawn significant attention to the development of quantum machine learning (QML). Reinforcement learning (R…
When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing
Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen +2
The rapid development of quantum computing has demonstrated many unique characteristics of quantum advantages, such as richer feature representation and more secured protection on…
Financial Vision Based Reinforcement Learning Trading Strategy
Yun-Cheng Tsai, Fu-Min Szu, Jun-Hao Chen +1
Recent advances in artificial intelligence (AI) for quantitative trading have led to its general superhuman performance in significant trading performance. However, the potential r…
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…
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…
Application of Quantum Machine Learning using the Quantum Variational Classifier Method to High Energy Physics Analysis at the LHC on IBM Quantum Computer Simulator and Hardware with 10 qubits
Sau Lan Wu, Jay Chan, Wen Guan +12
One of the major objectives of the experimental programs at the LHC is the discovery of new physics. This requires the identification of rare signals in immense backgrounds. Using…
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…
Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition
Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen +4
We propose a novel decentralized feature extraction approach in federated learning to address privacy-preservation issues for speech recognition. It is built upon a quantum convolu…
A Unified Framework for Quantum Supervised Learning
Nhat A. Nghiem, Samuel Yen-Chi Chen, Tzu-Chieh Wei
Quantum machine learning is an emerging field that combines machine learning with advances in quantum technologies. Many works have suggested great possibilities of using near-term…
Quantum Long Short-Term Memory
Samuel Yen-Chi Chen, Shinjae Yoo, Yao-Lung L. Fang
Long short-term memory (LSTM) is a kind of recurrent neural networks (RNN) for sequence and temporal dependency data modeling and its effectiveness has been extensively established…
Adversarial Robustness of Deep Convolutional Candlestick Learner
Jun-Hao Chen, Samuel Yen-Chi Chen, Yun-Cheng Tsai +1
Deep learning (DL) has been applied extensively in a wide range of fields. However, it has been shown that DL models are susceptible to a certain kinds of perturbations called \emp…