Quantum Machine Learning
521 papers for year 2024
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 61-72 of 521
Bee-yond the Plateau: Training QNNs with Swarm Algorithms
Rubén Darío Guerrero
Benchmarking quantum machine learning kernel training for classification tasks
Diego Alvarez-Estevez
Benchmarking Quantum Optimization by Traveling Salesman Problems
Richard H. Warren
Beyond full statevector simulation with Qibo
Andrea Pasquale, Andrea Papaluca, Renato M. S. Farias, Matteo Robbiati, Edoardo Pedicillo, Stefano Carrazza
BHT-QAOA: Generalizing Quantum Approximate Optimization Algorithm to Solve Arbitrary Boolean Problems as Hamiltonians
Ali Al-Bayaty, Marek Perkowski
Biclustering a dataset using photonic quantum computing
Ajinkya Borle, Ameya Bhave
Biclustering a dataset using photonic quantum computing
Ajinkya Borle, Ameya Bhave
BOOK REVIEW ON LANGUAGE(S) AND TRANSLATION BY MOHAMMED JADIR
SAID FATHI
Boosting the Validity of Multi-Class Quantum Outputs: Living on the Edge
Nathaniel Helgesen, Michael Felsberg, Jan-Åke Larsson
BRIDGING BORDERS: EXPAT TEACHERS NAVIGATING CROSS-CULTURAL CHALLENGES IN CHINA
LE ROUJIA, IREENA NASIHA IBNU, TENGKU ELENA TENGKU MAHAMAD
Building Continuous Quantum-Classical Bayesian Neural Networks for a Classical Clinical Dataset
Alona Sakhnenko, Julian Sikora, Jeanette Miriam Lorenz
Can Entanglement-enhanced Quantum Kernels Improve Data Classification?
Anand Babu, Saurabh G. Ghatnekar, Amit Saxena, Dipankar Mandal