Quantum Machine Learning
416 papers for year 2023
Quantum Machine Learning Research Context
This category covers quantum machine learning research, including quantum kernels, variational classifiers, hybrid learning systems, generative models, and QML benchmarks.
Showing 13-24 of 416
A general learning scheme for classical and quantum Ising machines
Ludwig Schmid, Enrico Zardini, Davide Pastorello
A Hybrid Classical-Quantum HPC Workload
Aniello Esposito, Sebastien Cabaniols, Jessica R. Jones, David Brayford
A hybrid quantum-classical conditional generative adversarial network algorithm for human-centered paradigm in cloud
Wenjie Liu, Ying Zhang, Zhiliang Deng, Jiaojiao Zhao, Lian Tong
A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery
L. Domingo, M. Chehimi, S. Banerjee, S. He Yuxun, S. Konakanchi, L. Ogunfowora, S. Roy, S. Selvaras, M. Djukic, C. Johnson
A Hyperparameter Study for Quantum Kernel Methods
Sebastian Egginger, Alona Sakhnenko, Jeanette Miriam Lorenz
A model that can be applied both online and face-to-face education: Problem based-quantum learning model
Burcu ÖKMEN, Şeyma ŞAHİN, Abdurrahman KILIÇ
A no free lunch theorem for untrained quantum circuits in machine learning
Steven Herbert
A novel feature selection method based on quantum support vector machine
Haiyan Wang
A Novel Image Classification Framework Based on Variational Quantum Algorithms
Yixiong Chen
A Novel Image Segmentation Algorithm based on Continuous-Time Quantum Walk using Superpixels
Wei-Min Shi, Feng-Xue Xu, Yi-Hua Zhou, Yu-Guang Yang
A Physics Lab Inside Your Head: Quantum Thought Experiments as an Educational Tool
Maria Violaris
A Post-Training Approach for Mitigating Overfitting in Quantum Convolutional Neural Networks
Aakash Ravindra Shinde, Charu Jain, Amir Kalev