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Computing Committor Functions for The Study of Rare Events Using Deep Learning
时间  Datetime
2019-12-24 14:00 — 15:00 
地点  Venue
5#306
报告人  Speaker
Weiqing Ren
单位  Affiliation
National University of Singapore
邀请人  Host
INS
报告摘要  Abstract

The committor function is a central object in understanding transition events between metastable states in complex systems. It has a very simple mathematical description – it satisfies the backward Kolmogorov equation. However, computing the committor function for realistic systems at low temperatures is a challenging task, due to the curse of dimensionality and the scarcity of transition data. In this talk, I will present a computational approach that overcomes these issues and achieves good performance on complex benchmark problems with rough energy landscapes. The new approach combines deep learning, importance sampling and feature engineering techniques. This establishes an alternative practical method for studying rare transition events among metastable states of complex, high dimensional systems.