Quantum Machine Learning
3,957 papers
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 613-624 of 3,957
Light cone cancellation for variational quantum eigensolver in solving noisy Max-Cut.
Lee X, Yan X, Xie N, Saito Y, Kurosawa L, Asai N, Cai D, Lau HC.
Light-addressable sandwich photoelectrochemical immunosensor array and lateral flow immunoassays with self-calibration using quantum dots-sensitized and porphyrin-engineered MOFs for accurate detection of amyloid β-proteins.
Wang L, Niu J, Chen X, Zhu Y, Hou X
Light-Weight Quantum Binary Image Classifier
Nagy M.
Lightweight quantum recurrent neural networks for time-series and dynamical systems
Yuan Chen, Abdul Khaliq
Lightweight Quantum-Enhanced ResNet for Coronary Angiography Classification: A Hybrid Quantum-Classical Feature Enhancement Framework
Jingsong Xia
Limitations and Potentials of Quantum Computing for InSAR Phase Unwrapping
Glatting, Kay, Meyer, Jan, Huber, Sigurd, Krieger, Gerhard
LLM-Guided Evolutionary Search for Algebraic T-Count Optimization
Daniil Fisher, Valentin Khrulkov, Mikhail Saygin, Ivan Oseledets, Stanislav Straupe
Local and Multi-Scale Strategies to Mitigate Exponential Concentration in Quantum Kernels
Claudia Zendejas-Morales, Debashis Saikia, Utkarsh Singh
Local Softmax and Global Weights in Non-Boolean Event Structures
Karl Svozil
Local surrogates for quantum machine learning
Nair SR, Ferrie C.
Local tensor-train surrogates for quantum learning models
Sreeraj Rajindran Nair, Christopher Ferrie
Long Range Frequency Tuning for QML
Michael Poppel, Jonas Stein, Sebastian Wölckert, Markus Baumann, Claudia Linnhoff-Popien