Category details:
In atomistic ML we face new challenges for post processing data. I would suggest this category to include existing tools from e.g. classical MD that can be used to post process MLIP trajectories but also new methods that are or will come up.
Personally, I am from the MD community, so I would suggest tools like:
Additional context:
In some form, this could be it's own awesome list but I think that evaluation of MLIP simulation data (MD, generative AI and other methods) is also an important topic and closely liked to atomistic ML and finding resources targeted towards the analysis can be difficult.
Would this fit the topic of this awesome list and what are your opinions?
Category details:
In atomistic ML we face new challenges for post processing data. I would suggest this category to include existing tools from e.g. classical MD that can be used to post process MLIP trajectories but also new methods that are or will come up.
Personally, I am from the MD community, so I would suggest tools like:
https://github.com/MDAnalysis/mdanalysis
https://mdtraj.readthedocs.io/en/latest/
https://www.ks.uiuc.edu/Research/vmd/ (more prominently visualisation)
most of https://www.mdanalysis.org/pages/mdakits/
Category Title: Simulation data post processing
Category Subtitle:
Additional context:
In some form, this could be it's own awesome list but I think that evaluation of MLIP simulation data (MD, generative AI and other methods) is also an important topic and closely liked to atomistic ML and finding resources targeted towards the analysis can be difficult.
Would this fit the topic of this awesome list and what are your opinions?