This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical
By Jason Brownlee on June 17, 2019 in Machine Learning Resources 4 Share Post Share I recently watched a Google Tech Talk with Eric Ladizinsky who visited the Quantum AI Lab at Google to talk about his D-Wave quantum computer. The talk is called Evolving Scalable Quantum Computers and is...
The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the ...
Despite the mounting anticipation for the quantum revolution, the success of quantum machine learning (QML) in the noisy intermediate-scale quantum (NISQ)
Classical optimization algorithms in machine learning often take a long time to compute when applied to a multi-dimensional problem and require a huge amount of CPU and GPU resource. Quantum parallelism has a potential to speed up machine learning algorithms. We describe a generic mathematical model...
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Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and studied extensivel
Table of ContentsChapter 1:Quantum Computing and Machine LearningChapter 2:Do Quantum Computers Really Exist?Chapter 3:It’s Not Trivial to Pick a QPUChapter 4:&l Download TXT Support All Device Epub iPhone/iPad/Android/Kindle PDF PC
Broughton M, Verdon G, McCourt T, Martinez AJ, Yoo JH, Isakov SV, Massey P, Halavati R, Niu MY, Zlokapa A et al (2020) Tensorflow quantum: a software framework for quantum machine learning. arXiv:2003.02989 Brown KL, Munro WJ, Kendon VM (2010) Using quantum computers for quantum si...
Dhaulakhandi R (2023) Quantum neural network architecture to perform machine learning tasks on NISQ computers. PhD thesis Djidjev HN, Chapuis G, Hahn G, Rizk G (2018) Efficient combinatorial optimization using quantum annealing. arXiv preprintarXiv:1801.08653 ...