Quantum Machine Learning
30 papers from OpenAlex
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 1-12 of 30
A Conceptual Thalamic Density × MA Model: Classical Low-Energy Coarse Classification for Initial Qualia as Dynamic Phase Flow and Local Entropy Resistance
仁定 五十嵐
A quantum computing approach for brain tumor image classification using amplitude encoding technique
Maheswari K.P., Kalaiselvi Thiruvenkadam, P. Sriramakrishnan
Absolute Coherence - Resonance over Resistance — a Conceptual Framework for Quantum Technologies
Hakan Henken
All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks
Richard DP East, Guillermo Alonso-Linaje, Chae-Yeun Park
Assessing the advantages and limitations of quantum neural networks in regression tasks
Gubio Gomes de Lima, Tiago de S. Farias, Alexandre C. Ricardo, Celso Jorge Villa Boas
Central Asian Influence in Modern Military Treatises: A Tutorial for Historiographical Implementation of Quantum Link Prediction
Jose Hernandez Perez
Codebase release 1.0 for QDFlow
Donovan Buterakos, Sandesh S. Kalantre, Joshua Ziegler, Jacob M. Taylor, Sanghyeok Park
DAGI–ESG Validation: MI Metric, GRR Time Dilation on ibm fez, and Einstein-Surrogate Closure in a 10k-Node Simulation
Petr Sramek
Density × MA: A Thalamic Model for Raw Qualia as Dynamic Phase Flow
仁定 五十嵐
Editorial: Nanomedicine targeting central nervous system
Zhixing Wu, Barkha J. Yadav-Samudrala, Sylvia Fitting
Explainable quantum convolutional neural network for attack detection in healthcare IoMT systems using SHAP and Grid5000 computing
M Y Amara, Sami Mnasri, M Y Amara, Thierry Val
Hybrid Quantum-Classical Training in Quantum Neural Networks: A Framework for Bridging Parameterized Quantum Circuits and Classical Optimization
Matthew Busel