SoK: quantum computing methods for machine learning optimization
H Baniata - Quantum Machine Intelligence, 2024 - Springer
Hyperparameter optimization (HPO) and neural architecture search (NAS) of machine
learning (ML) models are in the core implementation steps of AI-enabled systems. With multi …
learning (ML) models are in the core implementation steps of AI-enabled systems. With multi …
Quantum Circuit Training with Growth-Based Architectures
C Duffy, S Chaudhary, GV Velikova - arXiv preprint arXiv:2411.16560, 2024 - arxiv.org
This study introduces growth-based training strategies that incrementally increase
parameterized quantum circuit (PQC) depth during training, mitigating overfitting and …
parameterized quantum circuit (PQC) depth during training, mitigating overfitting and …
Redes neuronales quanvolucionales para clasificación de señal auditiva
A Leal Castaño - 2024 - docta.ucm.es
El principal objetivo de este trabajo es el estudio de técnicas de aprendizaje automático
cuántico (QML) para tareas de clasificación binaria, dirigidas esencialmente a señal …
cuántico (QML) para tareas de clasificación binaria, dirigidas esencialmente a señal …
[PDF][PDF] Growing Circuit Analysis
C Duffy, S Chaudhary, GV Velikova - indico.qtml2024.org
Quantum scientific machine learning (QSciML) addresses complex science and engineering
problems, including solving partial differential equations (PDEs). These problems often …
problems, including solving partial differential equations (PDEs). These problems often …