no code implementations • 10 Aug 2021 • Shuting Gu, Hongqiao Wang, Xiang Zhou
To reduce the number of expensive computations of the true gradients, we propose an active learning framework consisting of a statistical surrogate model, Gaussian process regression (GPR) for the energy function, and a single-walker dynamics method, gentle accent dynamics (GAD), for the saddle-type transition states.
1 code implementation • 29 Mar 2017 • Hongqiao Wang, Jinglai Li
In particular, we write the joint density approximately as a product of an approximate posterior density and an exponentiated GP surrogate.