1 citations · 1 across the 2 of their papers we have counts for
2 papers
quant-ph2023★ 1 cited
Towards Faster Reinforcement Learning of Quantum Circuit Optimization: Exponential Reward Functions
Ioana Moflic, Alexandru Paler
Reinforcement learning for the optimization of quantum circuits uses an agent whose goal is to maximize the value of a reward function that decides what is correct and what is wron…
quant-ph2023
Cost Explosion for Efficient Reinforcement Learning Optimisation of Quantum Circuits
Ioana Moflic, Alexandru Paler
Large scale optimisation of quantum circuits is a computationally challenging problem. Reinforcement Learning (RL) is a recent approach for learning strategies to optimise quantum…