Project ID: plumID:21.039
Name: Deep learning the slow modes for rare events sampling
Archive: https://github.com/maxbonomi/deep-learning-slow-modes/archive/main.zip (browse)
Category: methods
Keywords: collective variables, machine learning, slow modes, deep-tica, opes
PLUMED version: 2.8
Contributor: Luigi Bonati
Submitted on: 16 Sep 2021
Last revised: 09 Dec 2021
Publication: L. Bonati, G. Piccini, M. Parrinello, Deep learning the slow modes for rare events sampling. Proceedings of the National Academy of Sciences. 118 (2021)
PLUMED input files
Last tested: 22 Apr 2024, 20:57:00
Project description and instructions
Improve biased simulations by extracting slow modes that hinder convergence and accelerating them. This egg contains input files and data necessary to perform the exploratory simulations, train the neural network CVs and enhance their sampling. Note that some of the builds fail because PLUMED needs to be manually compiled against LibTorch. Code to train the Deep-TICA CVs and instructions for configuring PLUMED can be found on Github. More info about the method can be found here.
Submission history
[v1] 16 Sep 2021: original submission
[v2] 09 Dec 2021: updated doi
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