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 109-120 of 521
Directed st-connectivity with few paths is in quantum logspace
Simon Apers, Roman Edenhofer
Discovering emergent connections in quantum physics research via dynamic word embeddings
Felix Frohnert, Xuemei Gu, Mario Krenn, Evert van Nieuwenburg
Discovering Local Hidden-Variable Models for Arbitrary Multipartite Entangled States and Arbitrary Measurements
Nick von Selzam, Florian Marquardt
Discrete Randomized Smoothing Meets Quantum Computing
Tom Wollschläger, Aman Saxena, Nicola Franco, Jeanette Miriam Lorenz, Stephan Günnemann
Discrete-Time Quantum Walks: A Quantum Advantage for Graph Representation
Boxuan Ai
Disentanglement in dephasing channel with machine learning
Qihang Liu, Anran Qiao, Jung-Tsung Shen
Dissipation alters modes of information encoding in small quantum reservoirs near criticality
Krai Cheamsawat, Thiparat Chotibut
Distributed and Secure Kernel-Based Quantum Machine Learning
Arjhun Swaminathan, Mete Akgün
Distributed Partial Quantum Consensus of Qubit Networks With Connected Topologies.
Jin X, Cao Z, Tang Y, Kurths J.
Distributed Quantum Approximate Optimization Algorithm on a Quantum-Centric Supercomputing Architecture
Seongmin Kim, Vincent R. Pascuzzi, Zhihao Xu, Tengfei Luo, Eungkyu Lee, In-Saeng Suh
Distributed quantum machine learning via classical communication
Kiwmann Hwang, Hyang-Tag Lim, Yong-Su Kim, Daniel K Park, Yosep Kim
Do Quantum Neural Networks have Simplicity Bias?
Jessica Pointing