Codes supporting "Exploring Chemoinformatics Aspects of Few-shot Meta-learning by Example of Infinite Dilution Activity Coefficient in Ionic Liquids Prediction"
Authors/Creators
Description
Exploring Chemoinformatics Aspects of Few-shot Meta-learning by Example of Infinite Dilution Activity Coefficient in Ionic Liquids Prediction
Corresponding author: Karol Baran (GdańskTech), karol.baran[at]pg.edu.pl
Manuscript: doi.org/10.1021/acs.jcim.6c00067
Files and folders:
- data - directory with information on data and scripts to scrap data
- codes - directory with codes used in the study
Authors:
Karol Baran, Adam Kloskowski (GdańskTech)
2025 Gdańsk, Poland
repository maintained by Karol Baran
Acknowledgment:
The authors would like to gratefully acknowledge that this research was funded in whole or in part by the National Science Centre, Poland (NCN) under the Preludium 22 program in the years 2024–2027 (project no. UMO-2023/49/N/ST5/01043).
Files
kbarn411/maml-idac-il-v2.0.zip
Files
(23.5 kB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/kbarn411/maml-idac-il/tree/v2.0 (URL)
- Journal article: 10.1021/acs.jcim.6c00067 (DOI)
Funding
- National Science Centre
- Meta-learning as a machine learning tool for experimental boosting of sorption properties of ionic liquids UMO-2023/49/N/ST5/01043
Software
- Repository URL
- https://github.com/kbarn411/maml-idac-il