On-device training for robust variational quantum algorithms
Design of Variational Quantum Algorithm Program
As a data-driven approach, NAAS holistically composes highly matched accelerator and neural architectures together with efficient compiler mapping.
We develop a graph neural network and reinforcement learning based method for analog circuit transistor sizing.
We present Park, a platform for researchers to experiment with Reinforcement Learning (RL) for computer systems.
We develop a reinforcement learning framework for analog circuit design.