Data to support the article "Benchmarking machine-readable vectors of chemical reactions on computed activation barriers"

Data to support the article "Benchmarking machine-readable vectors of chemical reactions on computed activation barriers". This supports the github repository https://github.com/lcmd-epfl/benchmark-barrier-learning which contains the codes and duplicates the data.

The sub-directory "xyz" contains the xyz files for the three datasets. The sub-directory "properties" contains the corresponding computed properties.

The sub-directory "reps" contains the representations for all ML models used.

The sub-directory "model_outs" contains the output files/summaries of ML models trained.