Update README.md

README.md

@@ -90,7 +90,7 @@ Each GC layer performs the operation:
 
 $$H^{(l+1)} = \text{ReLU}\!\left(\hat{D}^{-1}\hat{A}\, H^{(l)}\, W^{(l)}\right)$$
 
-where $$\hat{A} = A + I$$ (adjacency with self-loops), $$\hat{D}$$ is the degree matrix of $$\hat{A}$$, $$H^{(l)}$$ is the node feature matrix at layer $$l$$, and $$W^{(l)}$$ is the learnable weight matrix.
+$$\text{where }\hat{A} = A + I \text{ (adjacency with self-loops) }, \hat{D} \text{ is the degree matrix of }\hat{A}, H^{(l)}\text{ is the node feature matrix at layer l, and }W^{(l)}\text{ is the learnable weight matrix.}$$
 
 ### Weight Tensors