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I have noticed that CatLearn includes both energy and forces in the training of a Gaussian process model, but only predicts energy from the GP model. The predicted forces are computed using finite differences according to Phys. Rev. Lett. 122, 156001 (2019) . However, predicting forces directly from the GP model is also starightforward once forces are included in the training just as what J. Chem. Phys. 147, 152720 (2017) did. Why not predicting forces directly from the GP model in CatLearn? Is there any benifit of using the finite difference approach?
Best,
Zeyuan
The text was updated successfully, but these errors were encountered:
Hi all,
I have noticed that CatLearn includes both energy and forces in the training of a Gaussian process model, but only predicts energy from the GP model. The predicted forces are computed using finite differences according to Phys. Rev. Lett. 122, 156001 (2019) . However, predicting forces directly from the GP model is also starightforward once forces are included in the training just as what J. Chem. Phys. 147, 152720 (2017) did. Why not predicting forces directly from the GP model in CatLearn? Is there any benifit of using the finite difference approach?
Best,
Zeyuan
The text was updated successfully, but these errors were encountered: