27 citations · 37 across the 28 of their papers we have counts for
29 papers
Transformers as Intrinsic Optimizers for Quantum Approximate Optimization Algorithm
Kuan-Cheng Chen, Xiaotian Xu, Hiromichi Matsuyama +3
The Quantum Approximate Optimization Algorithm (QAOA) is a leading variational framework for combinatorial optimization on noisy intermediate-scale quantum hardware, but its practi…
Scalable Quantum Machine Learning via Multi-layer Fully-Connected Variational Quantum Circuits
Howard Su, Chen-Yu Liu, Samuel Yen-Chi Chen +2
Variational quantum circuits (VQCs) face an expressivity-trainability dilemma and scalability challenges. We propose Multi-Layer Fully-Connected Variational Quantum Circuits (FC-VQ…
Federated Quantum Kernel Learning for Anomaly Detection in Multivariate IoT Time-Series
Kuan-Cheng Chen, Samuel Yen-Chi Chen, Chen-Yu Liu +1
The rapid growth of industrial Internet of Things (IIoT) systems has created new challenges for anomaly detection in high-dimensional, multivariate time-series, where privacy, scal…
Establishing Baselines for Photonic Quantum Machine Learning: Insights from an Open, Collaborative Initiative
Cassandre Notton, Vassilis Apostolou, Agathe Senellart +28
The Perceval Challenge is an open, reproducible benchmark designed to assess the potential of photonic quantum computing for machine learning. Focusing on a reduced and hardware-fe…
You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models
Chen-Yu Liu, Leonardo Placidi, Kuan-Cheng Chen +2
Quantum machine learning (QML) models conventionally rely on repeated measurements (shots) of observables to obtain reliable predictions. This dependence on large shot budgets lead…
Quantum Relational Knowledge Distillation
Chen-Yu Liu, Kuan-Cheng Chen, Keisuke Murota +2
Knowledge distillation (KD) is a widely adopted technique for compressing large models into smaller, more efficient student models that can be deployed on devices with limited comp…
Quantum Stochastic Walks for Portfolio Optimization: Theory and Implementation on Financial Networks
Yen Jui Chang, Wei-Ting Wang, Yun-Yuan Wang +3
Financial markets are noisy yet contain a latent graph-theoretic structure that can be exploited for superior risk-adjusted returns. We propose a quantum stochastic walk (QSW) opti…
Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting
Chen-Yu Liu, Kuan-Cheng Chen, Yi-Chien Chen +4
Typhoon trajectory forecasting is essential for disaster preparedness but remains computationally demanding due to the complexity of atmospheric dynamics and the resource requireme…
Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generation
Samuel Yen-Chi Chen, Chen-Yu Liu, Kuan-Cheng Chen +3
The rapid advancements in quantum computing (QC) and machine learning (ML) have led to the emergence of quantum machine learning (QML), which integrates the strengths of both field…
Learning to Learn with Quantum Optimization via Quantum Neural Networks
Kuan-Cheng Chen, Hiromichi Matsuyama, Wei-Hao Huang
Quantum Approximate Optimization Algorithms (QAOA) promise efficient solutions to classically intractable combinatorial optimization problems by harnessing shallow-depth quantum ci…
Federated Quantum-Train Long Short-Term Memory for Gravitational Wave Signal
Chen-Yu Liu, Samuel Yen-Chi Chen, Kuan-Cheng Chen +2
We present Federated QT-LSTM, a novel framework that combines the Quantum-Train (QT) methodology with Long Short-Term Memory (LSTM) networks in a federated learning setup. By lever…
Toward Large-Scale Distributed Quantum Long Short-Term Memory with Modular Quantum Computers
Kuan-Cheng Chen, Samuel Yen-Chi Chen, Chen-Yu Liu +1
In this work, we introduce a Distributed Quantum Long Short-Term Memory (QLSTM) framework that leverages modular quantum computing to address scalability challenges on Noisy Interm…
Resource-Efficient Compilation of Distributed Quantum Circuits for Solving Large-Scale Wireless Communication Network Problems
Kuan-Cheng Chen, Felix Burt, Shang Yu +3
Optimizing routing in Wireless Sensor Networks (WSNs) is pivotal for minimizing energy consumption and extending network lifetime. This paper introduces a resourceefficient compila…
Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning
Kuan-Cheng Chen, Samuel Yen-Chi Chen, Chen-Yu Liu +1
In this paper, we introduce Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning (Dist-QTRL), a novel approach to addressing the scalability challenges of traditional…
Programming Variational Quantum Circuits with Quantum-Train Agent
Chen-Yu Liu, Samuel Yen-Chi Chen, Kuan-Cheng Chen +2
In this study, the Quantum-Train Quantum Fast Weight Programmer (QT-QFWP) framework is proposed, which facilitates the efficient and scalable programming of variational quantum cir…
Quantum Kernel-Based Long Short-term Memory
Yu-Chao Hsu, Tai-Yu Li, Kuan-Cheng Chen
The integration of quantum computing into classical machine learning architectures has emerged as a promising approach to enhance model efficiency and computational capacity. In th…
Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection
Chu-Hsuan Abraham Lin, Chen-Yu Liu, Samuel Yen-Chi Chen +1
The rise of deepfake technologies has posed significant challenges to privacy, security, and information integrity, particularly in audio and multimedia content. This paper introdu…
CompressedMediQ: Hybrid Quantum Machine Learning Pipeline for High-Dimensional Neuroimaging Data
Kuan-Cheng Chen, Yi-Tien Li, Tai-Yu Li +3
This paper introduces CompressedMediQ, a novel hybrid quantum-classical machine learning pipeline specifically developed to address the computational challenges associated with hig…
Quantum-Train with Tensor Network Mapping Model and Distributed Circuit Ansatz
Chen-Yu Liu, Chu-Hsuan Abraham Lin, Kuan-Cheng Chen
In the Quantum-Train (QT) framework, mapping quantum state measurements to classical neural network weights is a critical challenge that affects the scalability and efficiency of h…
Noise-Aware Distributed Quantum Approximate Optimization Algorithm on Near-term Quantum Hardware
Kuan-Cheng Chen, Xiatian Xu, Felix Burt +3
This paper introduces a noise-aware distributed Quantum Approximate Optimization Algorithm (QAOA) tailored for execution on near-term quantum hardware. Leveraging a distributed fra…
Generalised Circuit Partitioning for Distributed Quantum Computing
Felix Burt, Kuan-Cheng Chen, Kin Leung
Distributed quantum computing (DQC) is a new paradigm aimed at scaling up quantum computing via the interconnection of smaller quantum processing units (QPUs). Shared entanglement…
Quantum Computing for Climate Resilience and Sustainability Challenges
Kin Tung Michael Ho, Kuan-Cheng Chen, Lily Lee +4
The escalating impacts of climate change and the increasing demand for sustainable development and natural resource management necessitate innovative technological solutions. Quant…
Quantum-Train Long Short-Term Memory: Application on Flood Prediction Problem
Chu-Hsuan Abraham Lin, Chen-Yu Liu, Kuan-Cheng Chen
Flood prediction is a critical challenge in the context of climate change, with significant implications for ecosystem preservation, human safety, and infrastructure protection. In…
QTRL: Toward Practical Quantum Reinforcement Learning via Quantum-Train
Chen-Yu Liu, Chu-Hsuan Abraham Lin, Chao-Han Huck Yang +2
Quantum reinforcement learning utilizes quantum layers to process information within a machine learning model. However, both pure and hybrid quantum reinforcement learning face cha…