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 325-336 of 3,957
DistributedEstimator: Distributed Training of Quantum Neural Networks via Circuit Cutting
Prabhjot Singh, Adel N. Toosi, Rajkumar Buyya
Distribution-Guided and Constrained Quantum Machine Unlearning
Nausherwan Malik, Zubair Khalid, Muhammad Faryad
Divide et impera: hybrid multinomial classifiers from quantum binary models
Simone Roncallo, Angela Rosy Morgillo, Seth Lloyd, Chiara Macchiavello, Lorenzo Maccone
Do Quantum Transformers Help? A Systematic VQC Architecture Comparison on Tabular Benchmarks
Chi-Sheng Chen, En-Jui Kuo
Do We Really Need Quantum Machine Learning?: A Multidimensional Empirical Study
Sudip Vhaduri, Ryan Gammon, Sayanton Dibbo
Does the diffuse OH-stretch band in the IR spectrum of protonated oxalate exhibit quantum chaos?
Qu C, Houston PL, Bowman JM
Double Descent in Quantum Kernel Ridge Regression
Kensuke Kamisoyama, Lento Nagano, Koji Terashi
dqc_simulator: an easy-to-use distributed quantum computing simulator
Kenny Campbell
dSABRE: A SABRE-Style Router for Multi-Core Distributed Quantum Computers
Sanjiang Li
Dual-emission carbon dots with UV-induced fluorescence enhancement: Construction of fluorescence sensor array and ratiometric probe for discrimination and detection of antibiotics.
Jia Y, Wang Y, Wang W, Wang S, Yang J
Dual-Energy X-ray Imaging Enabled by Passivated Bilayer Copper-Based Halide Scintillators.
Zhu Y, Liu C, Li Y, Li J, Lei W, Xu X, Chen J
Dual-mode sensor array based on silica-coated carbon dots with tunable fluorescence and phosphorescence for discrimination and detection of monoamine neurotransmitters.
Wang Y, Ning Y, Jia Y, Wang S, Wang W, Liang C, Ren Y