Equations look better now

Author: joaogui1

g3doc/tutorials/framework.md

@@ -18,8 +18,8 @@ forms besides the one illustrated above. For example, we can also select
 <img src="https://latex.codecogs.com/svg.latex?\(\sum_{x_j&space;\in&space;\mathcal{N}(x_i)}\mathcal{E}(y_i,g_\theta(x_j)\)" title="\(\sum_{x_j \in \mathcal{N}(x_i)}\mathcal{E}(y_i,g_\theta(x_j)\)"/>
  to be the
 neighbor loss, which calculates the distance between the ground truth
-![equation](http://www.sciweavers.org/tex2img.php?eq=%20%5C%28y_i%5C%29&bc=White&fc=Black&im=jpg&fs=12&ff=arev&edit=0)
-and the prediction from the neighbor ![equation](http://www.sciweavers.org/tex2img.php?eq=%5C%28g_%5Ctheta%28x_j%29%5C%29&bc=White&fc=Black&im=jpg&fs=12&ff=arev&edit=0).
+<img src="https://latex.codecogs.com/svg.latex?\(y_i\)" title="\(y_i\)" />
+and the prediction from the neighbor <img src="https://latex.codecogs.com/svg.latex?\(g_\theta(x_j)\)" title="\(g_\theta(x_j)\)" />.
  This is commonly used
 in adversarial learning
 [(Goodfellow et al., ICLR'15)](https://arxiv.org/pdf/1412.6572.pdf). Therefore,