63 | Engineer’s Guide to Machine Learning with Quantum Computers
Quantum computing lecture from the QuCS series.
47 | Quantum Machine Learning on Current Quantum Computers
Quantum computing lecture from the QuCS series.
36 | Hybrid Quantum-Classical Machine Learning with Applications
The development of machine learning (ML) and quantum computing (QC) hardware has generated a lot of interest in creating quantum machine learning (QML) applications.
34 | Optimize Quantum Learning on Near-Term Noisy Quantum Computers
In recent years, there has been a significant breakthrough in the development of superconducting quantum computers, with IBM’s 433-qubit quantum computer being a prime example of the progress made in addressing scalability issues.
21 | Quantum Machine Learning: Theoretical Foundations and Applications on NISQ Devices
Quantum machine learning (QML) is a trailblazing research subject that integrates quantum computing and machine learning.
20 | Learning and Training in Quantum Environments
Quantum computing presents fascinating new opportunities for various applications, including machine learning, simulation, and optimization.
6 | Adaptive Online Learning of Quantum States
Shadow tomography is a fundamental problem in quantum computing, whose goal is to efficiently learn an unknown d-dimensional quantum state using projective measurements.