Representing crystal structures is crucial for enabling the inverse design of materials with desired properties via machine learning. Here, the authors propose a versatile crystal structure representation based on continuous fields rather than grid-based discretization, overcoming the tradeoff between spatial resolution and computational complexity.
- Naoya Chiba
- Yuta Suzuki
- Kanta Ono
