Quantum Machine Learning
416 papers for year 2023
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 373-384 of 416
The Application of Eco-Edutainment-Based Quantum Teaching Model to the Learning Outcome of Non-formal Education Study Programme Students
Sofino, Ririn Gusti, Bayu Pradikto
The Automated Bias Triangle Feature Extraction Framework
Madeleine Kotzagiannidis, Jonas Schuff, Nathan Korda
The exact evaluation of hexagonal spin-networks and topological quantum neural networks
Matteo Lulli, Antonino Marciano, Emanuele Zappala
The Gell-Mann feature map of qutrits and its applications in classification tasks
T. Valtinos, A. Mandilara, D. Syvridis
The History of Quantum Games
Laura Piispanen, Edward Morrell, Solip Park, Marcell Pfaffhauser, Annakaisa Kultima
The Physics of Preference: Unravelling Imprecision of Human Preferences through Magnetisation Dynamics
Ivan S. Maksymov, Ganna Pogrebna
The power of one clean qubit in supervised machine learning.
Karimi M, Javadi-Abhari A, Simon C, Ghobadi R.
The Quantum House Of Cards
Xavier Waintal
The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not)
Sukwoong Choi, William S. Moses, Neil Thompson
The role of data embedding in equivariant quantum convolutional neural networks
Sreetama Das, Stefano Martina, Filippo Caruso
The role of si raca app in quantum learning to improve students' motivation and reading achievement
Cahyo Hasanudin, Ayu Fitrianingsih, Nofia Fitriyana, Moh. Dika Hermanto, Heny Kusuma Widyaningrum
The six blinds and the elephant or an interdisciplinary selection of measurement features
Ask Ellingsen, Douglas Lundholm, Jean-Pierre Magnot