8 citations · 29 across the 48 of their papers we have counts for
6 papers · 1 filter
Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning
Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang +16
Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states. Quantum FWPs (QFWPs) extend this idea with v…
Toward Generative Quantum Utility via Correlation-Complexity Map
Chen-Yu Liu, Leonardo Placidi, Eric Brunner +1
We study a practical question in generative quantum machine learning: given a classical dataset, can we determine, before training, whether it is well suited to a quantum generativ…
Tensor Network Generator-Enhanced Optimization for Traveling Salesman Problem
Ryo Sakai, Chen-Yu Liu
We present an application of the tensor network generator-enhanced optimization (TN-GEO) framework to address the traveling salesman problem (TSP), a fundamental combinatorial opti…
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…
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…
Joint Tensor-Train Parameterization for Efficient and Expressive Low-Rank Adaptation
Jun Qi, Chen-Yu Liu, Sabato Marco Siniscalchi +2
Low-Rank Adaptation (LoRA) is widely recognized for its parameter-efficient fine-tuning of large-scale neural models. However, standard LoRA independently optimizes low-rank matric…