Kim E. Jelfs

According to our database, Kim E. Jelfs authored at least 9 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2025

The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning.

Toby Boyne, Juan S. Campos, Becky D. Langdon, Jixiang Qing, Yilin Xie, Shiqiang Zhang, Calvin Tsay, Ruth Misener, Daniel W. Davies, Kim E. Jelfs, Sarah Boyall, Thomas M. Dixon, Linden Schrecker, Jose Pablo Folch

CoRR, June, 2025

2024

Enhancing discovery of host-guest binders.

Gokay Avci, Kim E. Jelfs

Nat. Comput. Sci., 2024

Applying Multi-Fidelity Bayesian Optimization in Chemistry: Open Challenges and Major Considerations.

Edmund Judge, Mohammed Azzouzi, Austin M. Mroz, Antonio del Rio-Chanona, Kim E. Jelfs

CoRR, 2024

PolyCL: Contrastive Learning for Polymer Representation Learning via Explicit and Implicit Augmentations.

Jiajun Zhou, Yijie Yang, Austin M. Mroz, Kim E. Jelfs

CoRR, 2024

2021

HCGA: Highly comparative graph analysis for network phenotyping.

Robert L. Peach, Alexis Arnaudon, Julia A. Schmidt, Henry A. Palasciano, Nathan R. Bernier, Kim E. Jelfs, Sophia N. Yaliraki, Mauricio Barahona

Patterns, 2021

Materials Precursor Score: Modeling Chemists' Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors.

Steven Bennett, Filip T. Szczypinski, Lukas Turcani, Michael E. Briggs, Rebecca L. Greenaway, Kim E. Jelfs

J. Chem. Inf. Model., 2021

2018

High-Throughput Screening Approach for the Optoelectronic Properties of Conjugated Polymers.

Liam Wilbraham, Enrico Berardo, Lukas Turcani, Kim E. Jelfs, Martijn A. Zwijnenburg

J. Chem. Inf. Model., 2018

pywindow: Automated Structural Analysis of Molecular Pores.

Marcin Miklitz, Kim E. Jelfs

J. Chem. Inf. Model., 2018

stk: A python toolkit for supramolecular assembly.

Lukas Turcani, Enrico Berardo, Kim E. Jelfs

J. Comput. Chem., 2018