56 citations · 209 across the 13 of their papers we have counts for
3 papers · 1 filter
Combining Reinforcement Learning and Tensor Networks, with an Application to Dynamical Large Deviations
Edward Gillman, Dominic C. Rose, Juan P. Garrahan
We present a framework to integrate tensor network (TN) methods with reinforcement learning (RL) for solving dynamical optimisation tasks. We consider the RL actor-critic method, a…
Using (1 + 1)D Quantum Cellular Automata for Exploring Collective Effects in Large Scale Quantum Neural Networks
Edward Gillman, Federico Carollo, Igor Lesanovsky
Central to the field of quantum machine learning is the design of quantum perceptrons and neural network architectures. A key question in this regard is the impact of quantum effec…
Asynchronism and nonequilibrium phase transitions in D quantum cellular automata
Edward Gillman, Federico Carollo, Igor Lesanovsky
Probabilistic cellular automata provide a simple framework for the exploration of classical nonequilibrium processes. Recently, quantum cellular automata have been proposed that re…