Course

Generative modelling: Hopfield networks, Boltzmann machines and restricted Boltzmann machines (RBMs)

SO(10) and Pati-Salam GUT

Propagation of strings in curved space-time; Compactification and T-duality.

Reinforcement learning: Q-learning, Bellman equations

SU(5) Grand Unification Theory

An interesting scattering amplitue: n-point tree-level amplitude

Reinforcement learning: Markov decision processes, policy gradient methods

Anomalies in the Standard Model

Dimensional reduction using t-distributed stochastic neighbour embedding (t-SNE); Kullback-Liebler (KL) divergence; maximum likelihood estimation

The state-operator map and sphere correlation function

States and Operators