Supervised learning - Convolutional networks for hyper-resolution of scientific images, the case of galaxy classification, graph neural networks, automated discovery of physical laws by symbolic models
Unsupervised learning – The Ising model, Markov chains, Metropolis algorithm, Gibbs sampling. Restricted Boltzmann machines for unsupervised learning. Autoencoders.
Reinforcement learning - Bellman equation, Reinforcement learning algorithms, density matrix formalism, master equation of quantum systems, coherent control of quantum states
Quantum Machine Learning: quantum generative adversarial networks for generation of approximated distributions, training of variational quantum circuits for generation of entangled data, quantum support vector machines
Epistemological aspects