Quantum Machine Learning
4,265 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 205-216 of 4,265
Benchmarking deep and hybrid quantum classical models for Gallo Roman ceramic sherd classification
CHAIDRON C, Imrani HT.
Benchmarking Encoding Families in Quantum Neural Networks Under Fixed Circuit Area for Frequency Spectrum and Trainability
Martyna Czuba, Patrick Holzer, Hein Zay Yar Oo
Benchmarking fault-tolerant quantum computing hardware via QLOPS
Linghang Kong, Fang Zhang, Jianxin Chen
Benchmarking loss functions for trainable quantum feature maps
Nguyen Dinh Quyen, Vu Tuan Hai, Quoc Chuong Nguyen, Le Bin Ho, Lan Nguyen Tran
Benchmarking Quantum and Classical Machine Learning Models on Oncological Data
Sydney Leither, Thomas Lubinski, Michael Kubal, Sonika Johri
Benchmarking Quantum Annealing for a Greenhouse-Inspired Control QUBO
Hamzeh Alavirad, Maryam Bahrami Zanjani
Benchmarking Quantum Feature Encoding Strategies for Binary Classification with QSVM
Murat Kurt
Benchmarking Quantum Kernel Support Vector Machines Against Classical Baselines on Tabular Data: A Rigorous Empirical Study with Hardware Validation
Siavash Kakavand, Christoph Strohmeyer, Michael Schlotter
Benchmarking quantum kernels and modern vision models for compound facial expression recognition.
Florestiyanto MY, Surjono HD, Jati H.
Benchmarking Quantum Machine Learning for Power-System Attack Detection: Evaluation Choices Decide the Outcome Before the Models Do
Md Rezwanul Islam
Benchmarking the Lights Out Problem on Real Quantum Hardware
Maksims Dimitrijevs, Maria Palchiha, Abuzer Yakaryilmaz
Benchmarking the ORCA PT-2 Boson Sampler using Minimum Dominating Set Problems
Jessica Park, Susan Stepney, Irene D'Amico