DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.
The documentation of DeepH-pack, the latest iteration of DeepH, unites all the preceding DeepH methodologies into a cohesive package. This advanced version has been meticulously rewritten with JAX, enhancing its efficiency and capabilities.
