Published June 4, 2026 | Version v2.0

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

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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