Covers Markov chain Monte Carlo and neural networks' role in quantum states representation and ground state approximation for frustrated spins systems.
Covers Markov Chain Monte Carlo for sampling high-dimensional distributions, discussing challenges, advantages, and applications like the Knapsack Problem and cryptography.
