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
IEPDYN: Integral-equation formalism of population dynamics
Kento Kasahara, Ryo Okabe, Chia-en A. Chang +2
We propose the integral-equation formalism of population dynamics (IEPDYN) to describe the population dynamics of distinct configurational states. According to classical reaction d…
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…