Synergistic Modeling of Liquid Properties: Integrating Neural Network-Derived Molecular Features with Modified Kernel Models
Unveiling Molecular Moieties through Hierarchical Graph Explainability
Reaction Rebalancing: A Novel Approach to Curating Reaction Databases
Towards the Prediction of Drug Solubility in Binary Solvent Mixtures at Various Temperatures Using Machine Learning
Evaluation of Reinforcement Learning in Transformer-based Molecular Design
EC-Conf: A ultra-fast diffusion model for molecular conformation generation with equivariant consistency
FS-mutant: A Few-shot Learning Benchmark for Protein Mutants Mining
MolNexTR: A Generalized Deep Learning Modelfor Molecular Image Recognition
Accurate Prediction of Protein-Ligand Interactions by Combining Physical Energy Functions and Graph-Neural Networks
Learning symmetry-aware atom mapping in chemical reactions through deep graph matching