CompRhys/aviary
The Wren sits on its Roost in the Aviary.
Unified framework implementing three complementary deep learning architectures for materials property prediction: coordinate-free models (Roost, Wren, WrenFormer) that require only elemental composition, and structure-based CGCNN that leverages pymatgen-parsed crystal structures. Supports both CLI and Python APIs for training, evaluation, and inference across regression and classification tasks with configurable loss functions and robustness options on materials datasets in CSV/JSON formats.
Stars
61
Forks
13
Language
Python
License
MIT
Category
Last pushed
Jan 06, 2026
Commits (30d)
0
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