Learning Molecular Dynamics with Simple Language Model built upon Long Short-Term Memory Neural Network

26 Apr 2020 Sun-Ting Tsai En-Jui Kuo Pratyush Tiwary

Recurrent neural networks (RNNs) have led to breakthroughs in natural language processing and speech recognition, wherein hundreds of millions of people use such tools on a daily basis through smartphones, email servers and other avenues. In this work, we show such RNNs, specifically Long Short-Term Memory (LSTM) neural networks can also be applied to capturing the temporal evolution of typical trajectories arising in chemical and biological physics... (read more)

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