collective variables 1committor 1deep learning 1explainable AI 1molecular dynamics 1reaction coordinate 1
From the 1 of 3 linked papers with an AI index.
3 papers
physics.chem-ph2026
Deep learning of committor and explainable artificial intelligence analysis for identifying reaction coordinates
Toshifumi Mori, Kei-ichi Okazaki, Kang Kim +1
The paper presents a framework that uses deep neural networks to learn the committor function for identifying reaction coordinates in complex molecular systems, and applies explain…
physics.chem-ph2026
Deep learning of committor for ion dissociation and interpretable analysis of solvent effects using atom-centered symmetry functions
Kenji Okada, Kazushi Okada, Kei-ichi Okazaki +3
The association and dissociation of ion pairs in water are fundamental to physical chemistry, yet their reaction coordinates are complex, involving not only interionic distance but…
physics.chem-ph2025
Investigating the hyperparameter space of deep neural network models for reaction coordinates
Kyohei Kawashima, Takumi Sato, Kei-ichi Okazaki +3
Identifying reaction coordinates (RCs) is a key to understanding the mechanism of reactions in complex systems. Deep neural network (DNN) and machine learning approaches have becom…