3 papers
physics.chem-ph2026
ChemFlow:A Hierarchical Neural Network for Multiscale Representation Learning in Chemical Mixtures
Jinming Fan, Chao Qian, Wilhelm T. S. Huck +2
Accurate prediction of the physicochemical properties of molecular mixtures using graph neural networks remains a significant challenge, as it requires simultaneous embedding of in…
q-bio.MN2025
Modelling Chemical Reaction Networks using Neural Ordinary Differential Equations
Anna C. M. Thöni, William E. Robinson, Yoram Bachrach +2
In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordina…
cs.LG2023
Explainability Techniques for Chemical Language Models
Stefan Hödl, William Robinson, Yoram Bachrach +2
Explainability techniques are crucial in gaining insights into the reasons behind the predictions of deep learning models, which have not yet been applied to chemical language mode…