anew

_posts/2023-08-01-mace.md

@@ -14,13 +14,13 @@ toc: true
 MACE (Message Passing Atomic Cluster Expansion) is an equivariant message passing neural network that uses higher-order messages to enhance the accuracy and efficiency of force fields in computational chemistry.
 
 ### **Node Representation**
-Each node $\large{i}$ is represented by:
+Each node $$\large{i}$$ is represented by:
 
 $$
 \large{\sigma_i^{(t)} = (r_i, z_i, h_i^{(t)})}
 $$
 
-where $r_i \in \mathbb{R}^3$ is the position, $\large{z_i}$ is the chemical element, and $\large{h_i^{(t)}}$ are the learnable features at layer $\large{t}$.
+where $$r_i \in \mathbb{R}^3$$ is the position, $$\large{z_i}$$ is the chemical element, and $$\large{h_i^{(t)}}$$ are the learnable features at layer $$\large{t}$$.
 
 ### **Message Construction**
 Messages are constructed hierarchically using a body order expansion: