no code implementations • 13 Oct 2023 • Hardeep Bassi, Yuanran Zhu, Senwei Liang, Jia Yin, Cian C. Reeves, Vojtech Vlcek, Chao Yang
In this paper, we propose using LSTM-RNNs (Long Short-Term Memory-Recurrent Neural Networks) to learn and represent nonlinear integral operators that appear in nonlinear integro-differential equations (IDEs).
no code implementations • 27 May 2023 • Senwei Liang, Aditya N. Singh, Yuanran Zhu, David T. Limmer, Chao Yang
We propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths.
1 code implementation • 24 Feb 2022 • Yuanran Zhu, Yu-Hang Tang, Changho Kim
We devise mechanisms for training the neural network model to reproduce the correct \emph{statistical} behavior of a target stochastic process.
no code implementations • 21 Mar 2021 • Yu-Hang Tang, Yuanran Zhu, Wibe A. de Jong
Optimizing the noise model using maximum likelihood estimation leads to the containment of the GPR model's predictive error by the posterior standard deviation in leave-one-out cross-validation.