no code implementations • 3 Dec 2020 • Siu Wun Cheung, Eric Chung, Yalchin Efendiev, Wing Tat Leung, Sai-Mang Pun
The iterative procedure starts with the construction of an energy minimizing snapshot space that can be used for approximating the solution of the model problem.
Numerical Analysis Numerical Analysis
no code implementations • 17 Nov 2020 • Eric Chung, Yalchin Efendiev, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
In this work, we propose a multi-agent actor-critic reinforcement learning (RL) algorithm to accelerate the multi-level Monte Carlo Markov Chain (MCMC) sampling algorithms.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 31 Aug 2020 • Boris Chetverushkin, Eric Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
This multiscale problem is interesting from a multiscale methodology point of view as the model problem has a hyperbolic multiscale term, and designing multiscale methods for hyperbolic equations is challenging.
Numerical Analysis Numerical Analysis 65M22, 65M60
no code implementations • 13 Jun 2018 • Yating Wang, Siu Wun Cheung, Eric T. Chung, Yalchin Efendiev, Min Wang
Numerical results show that using deep learning and multiscale models, we can improve the forward models, which are conditioned to the available data.