Minor fix for paper reference
Browse files
README.md
CHANGED
|
@@ -16,7 +16,7 @@ tags:
|
|
| 16 |
In pursuit of the universal functional for density functional theory
|
| 17 |
(DFT), the OneDFT team from Microsoft Research AI for Science has
|
| 18 |
developed the Skala-1.0 exchange-correlation functional, as introduced
|
| 19 |
-
in [Accurate and scalable exchange-correlation with deep learning,
|
| 20 |
Luise et al. 2025](https://arxiv.org/abs/2506.14665v5). This
|
| 21 |
approach departs from the traditional route of incorporating
|
| 22 |
increasingly expensive hand-designed non-local features from Jacob\'s
|
|
@@ -203,7 +203,7 @@ The training datapoints are preprocessed as follows.
|
|
| 203 |
|
| 204 |
The training hyperparameter settings are detailed in the supplementary
|
| 205 |
material of [Accurate and scalable exchange-correlation with deep
|
| 206 |
-
learning, Luise et al. 2025](https://arxiv.org/abs/2506.14665v5).
|
| 207 |
|
| 208 |
#### Speeds, sizes, times
|
| 209 |
|
|
|
|
| 16 |
In pursuit of the universal functional for density functional theory
|
| 17 |
(DFT), the OneDFT team from Microsoft Research AI for Science has
|
| 18 |
developed the Skala-1.0 exchange-correlation functional, as introduced
|
| 19 |
+
in [Accurate and scalable exchange-correlation with deep learning (arXiv v5),
|
| 20 |
Luise et al. 2025](https://arxiv.org/abs/2506.14665v5). This
|
| 21 |
approach departs from the traditional route of incorporating
|
| 22 |
increasingly expensive hand-designed non-local features from Jacob\'s
|
|
|
|
| 203 |
|
| 204 |
The training hyperparameter settings are detailed in the supplementary
|
| 205 |
material of [Accurate and scalable exchange-correlation with deep
|
| 206 |
+
learning (arXiv v5), Luise et al. 2025](https://arxiv.org/abs/2506.14665v5).
|
| 207 |
|
| 208 |
#### Speeds, sizes, times
|
| 209 |
|