3 citations · 4 across the 17 of their papers we have counts for
7 papers · 1 filter
DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search
Jiayang Niu, Yan Wang, Jie Li +4
Reinforcement-learning-based quantum architecture search (RL-QAS) repeatedly invokes a variational quantum eigensolver (VQE) after each gate addition even though circuit transition…
Geometric and Quantum Kernel Methods for Predicting Skeletal Muscle Outcomes in chronic obstructive pulmonary disease
Azadeh Alavi, Hamidreza Khalili, Stanley H. Chan +3
Chronic obstructive pulmonary disease (COPD) affects hundreds of millions of people worldwide, and skeletal-muscle dysfunction is clinically important. Quantum machine learning is…
Practical Quantum-Classical Feature Fusion for complex data Classification
Azadeh Alavi, Fatemeh Kouchmeshki, Abdolrahman Alavi
Hybrid quantum and classical learning aims to couple quantum feature maps with the robustness of classical neural networks, yet most architectures treat the quantum circuit as an i…
A Unified Contrastive-Generative Framework for Time Series Classification
Ziyu Liu, Azadeh Alavi, Minyi Li +1
Self-supervised learning (SSL) for multivariate time series mainly includes two paradigms: contrastive methods that excel at instance discrimination and generative approaches that…
Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification
Ziyu Liu, Azadeh Alavi, Minyi Li +1
Self-supervised contrastive learning has become a key technique in deep learning, particularly in time series analysis, due to its ability to learn meaningful representations witho…
Leveraging SPD Matrices on Riemannian Manifolds in Quantum Classical Hybrid Models for Structural Health Monitoring
Azadeh Alavi, Sanduni Jayasinghe
Realtime finite element modeling of bridges assists modern structural health monitoring systems by providing comprehensive insights into structural integrity. This capability is es…
Self-Supervised Learning for Time Series: Contrastive or Generative?
Ziyu Liu, Azadeh Alavi, Minyi Li +1
Self-supervised learning (SSL) has recently emerged as a powerful approach to learning representations from large-scale unlabeled data, showing promising results in time series ana…