/awesome-quantum-ml

Curated list of awesome papers and resources in quantum machine learning

Awesome Quantum Machine Learning

A list of awesome papers and cool resources in the field of quantum machine learning (machine learning algorithms running on quantum devices). It does not include the use of classical ML algorithms for quantum purpose. Don't hesitate to suggest resources I could have forgotten (I take pull requests).

Papers

Reviews

Discrete-variables quantum computing

Theory

Variational circuits

Variational circuits are quantum circuits with variable parameters that can be optimized to compute a given function. They can for instance be used to classify or predict properties of quantum and classical data, sample over complicated probability distributions (as generative models), or solve optimization and simulation problems.

QRAM-based quantum ML

Tensor Networks

Reinforcement learning

Optimization

Kernel methods and SVM

Quantum circuits that are used to extract features from data or to improve kernel-based ML algorithms in general:

Dequantization of quantum ML

Kingdom of Ewin Tang. Papers showing that a given quantum machine learning algorithm does not lead to any improved performance compared to a classical equivalent (either asymptotically or including constant factors):

Continuous-variables quantum computing

Variational circuits

Kernel methods and SVM

Other awesome lists