From the 2 of 4 papers with an AI index.
1 citations
- The Graduate University for Advanced Studies, SOKENDAIJP2 papers
- Chinese Academy of SciencesCN1 paper
- Jeonbuk National UniversityKR1 paper
- Korea Institute for Advanced StudyKR1 paper
- Kyoto UniversityJP1 paper
- Kyushu UniversityJP1 paper
- Lund UniversitySE1 paper
- Osaka University of EconomicsJP1 paper
- Seoul National UniversityKR1 paper
- The Open University of JapanJP1 paper
- The University of OsakaJP1 paper
- Tokyo University of ScienceJP1 paper
4 papers · 1 filter
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…
Analytical Nuclear Gradients for State-Averaged Configuration Interaction Singles Variants: Application to Conical Intersections
Takashi Tsuchimochi
We derive analytical nuclear gradients for state-averaged orbital-optimized configuration interaction singles (SACIS) and its spin-projected extension (SAECIS), enabling efficient…
Leveraging configuration interaction singles for qualitative descriptions of ground and excited states: state-averaging, linear-response, and spin-projection
Takashi Tsuchimochi, Benjamin Mokhtar
While configuration interaction singles (CIS) provides a computationally efficient description of excited states, it systematically overestimates excitation energies and performs p…
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…