April 2026 monthly summary for facebookresearch/fairchem: Delivered the AllScAIP attention-based interatomic potential model for molecular simulations, with YAML-driven configuration for model parameters and dataset handling, plus Python modules for model architecture and training setup. Extended the inference path to support max-atom padding via a new config. The work aligns with the published paper (arXiv:2603.06567) and includes tests ensuring compatibility with prior work (#1326). No critical bugs reported; continued emphasis on reproducibility and quality.

February 2026 monthly summary focusing on metric correctness and reliability in FairChem. Fixed a broadcasting bug in per_atom_mae and per_atom_mse that previously produced incorrect 2-D outputs due to an unnecessary unsqueeze operation. This change ensures 1-D metric vectors are returned and accurately aggregated, improving the fidelity of energy-prediction error metrics and the trustworthiness of model evaluation.

Monthly summary for 2025-09 focusing on business value and technical achievements for FAIR-Chem/fairchem.

March 2025 — FAIR-Chem/fairchem: Key reliability improvement in experiment logging. Implemented a TensorBoard logging robustness fix to ensure stable metric capture across diverse logger configurations. Specifically, the fix handles non-dictionary logger configurations and defaults to -1 for non-wandb loggers to prevent errors, enhancing overall logging stability during model evaluation.