Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step Retrosynthesis

Documenti analoghi

• UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
  di: Zeng, Kaipeng, et al.
  Pubblicazione: (2024)
• From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
  di: Min, Yaosen, et al.
  Pubblicazione: (2022)
• Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials
  di: Fu, Cong, et al.
  Pubblicazione: (2025)
• Advances in the Simulation and Modeling of Complex Systems using Dynamical Graph Grammars
  di: Medwedeff, Eric, et al.
  Pubblicazione: (2024)
• Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics
  di: Sun, Fang, et al.
  Pubblicazione: (2024)