Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey
Deep reinforcement learning has led to dramatic breakthroughs in the field of artificial
intelligence for the past few years. As the amount of rollout experience data and the size of …
intelligence for the past few years. As the amount of rollout experience data and the size of …
TorchQC-A framework for efficiently integrating machine and deep learning methods in quantum dynamics and control
Abstract Machine learning has been revolutionizing our world over the last few years and is
also increasingly exploited in several areas of physics, including quantum dynamics and …
also increasingly exploited in several areas of physics, including quantum dynamics and …
Generalizing in Net-Zero Microgrids: A Study with Federated PPO and TRPO
This work addresses the challenge of optimal energy management in microgrids through a
collaborative and privacy-preserving framework. We propose the FedTRPO methodology …
collaborative and privacy-preserving framework. We propose the FedTRPO methodology …
ShortCircuit: AlphaZero-Driven Circuit Design
Chip design relies heavily on generating Boolean circuits, such as AND-Inverter Graphs
(AIGs), from functional descriptions like truth tables. This generation operation is a key …
(AIGs), from functional descriptions like truth tables. This generation operation is a key …
ShortCircuit: AlphaZero-Driven Generative Circuit Design
Chip design relies heavily on generating Boolean circuits, such as AND-Inverter Graphs
(AIGs), from functional descriptions like truth tables. This generation operation is a key …
(AIGs), from functional descriptions like truth tables. This generation operation is a key …