Deep neural networks for density functional theory Hamiltonian.
Extended DeepH (xDeepH) method for magnetic materials.
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.
Add a description, image, and links to the deeph topic page so that developers can more easily learn about it.
To associate your repository with the deeph topic, visit your repo's landing page and select "manage topics."