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Active Learning for Saddle Point Calculation
v1v2 (latest)

Active Learning for Saddle Point Calculation

10 August 2021
Shuting Gu
Hongqiao Wang
Xiaoping Zhou
ArXiv (abs)PDFHTML

Papers citing "Active Learning for Saddle Point Calculation"

6 / 6 papers shown
Title
Explicit Estimation of Derivatives from Data and Differential Equations
  by Gaussian Process Regression
Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression
Hongqiao Wang
Xiang Zhou
15
15
0
13 Apr 2020
Computing Committor Functions for the Study of Rare Events Using Deep
  Learning
Computing Committor Functions for the Study of Rare Events Using Deep Learning
Qianxiao Li
Bo Lin
W. Ren
56
68
0
14 Jun 2019
Active Learning of Uniformly Accurate Inter-atomic Potentials for
  Materials Simulation
Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation
Linfeng Zhang
De-Ye Lin
Han Wang
R. Car
E. Weinan
46
336
0
28 Oct 2018
Less is more: sampling chemical space with active learning
Less is more: sampling chemical space with active learning
Justin S. Smith
B. Nebgen
Nicholas Lubbers
Olexandr Isayev
A. Roitberg
57
616
0
28 Jan 2018
Gaussian process surrogates for failure detection: a Bayesian
  experimental design approach
Gaussian process surrogates for failure detection: a Bayesian experimental design approach
Hongqiao Wang
Guang Lin
Jinglai Li
34
38
0
11 Sep 2015
Simulation-based optimal Bayesian experimental design for nonlinear
  systems
Simulation-based optimal Bayesian experimental design for nonlinear systems
Xun Huan
Youssef M. Marzouk
81
429
0
20 Aug 2011
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