Jan Weinreich

thank you getting started right away!

Work is in full progress! However, we wanted to notify you that we are considering pivoting to a different target: Instead of predicting the toxicity of a compound, we would...

thank you, I made the minor changes to the main post of this issue. Most of the code is there we just need to clean and document it well. Will...

Thanks for your feedback! - I will get to the points as soon as possible. All the aspects about references and visual adjustments will be fixed. - About the expected...

Sure I can see if these molecules are in the test set and add the reference values. No problem, rerunning the models as I write with new version of concrete-ml....

Thank you for your patience @bcm-at-zama ! ### Fixes 1) Fixed spelling 2) The "popular" molecules aspirin and ibuprofen are not in the dataset: we cannot compare against these values....

Hey could you test if you still get the same numbers with all the new changes that happened in the meantime? I agree it might make sense to break down...

Great I started working on the SN2-20 dataset (https://iopscience.iop.org/article/10.1088/2632-2153/aba822/meta), was not published as smiles as far as I know so have to transform fist to smiles, then reaction smiles and...

Ok to summarize: the performance is not great! Below I evaluate the performance on a subset of SN2-20 reaction energies.  REACT SMILES are reaction smiles e.g. for SN2: `[H]C([H])([H])C([H])([H])F.H>>[H]C([H])([H])C([H])([H])[H].F`...

1) For the FPS ("fingerprints"), I first compute the bit representation using `fps, mapping = DrfpEncoder.encode(REACT_SMILES, mapping=True, n_folded_length=512)` resulting in an array like this: ` array([['0', '0', '0', ..., '0',...