diff --git a/README.md b/README.md index 3276fea..116fb09 100644 --- a/README.md +++ b/README.md @@ -105,7 +105,7 @@ In this section, we first introduce the concept of relevance score with Sensitiv ## 3 Gradient Based Methods -In this section, we explore various types of gradient-based visualization methods such as Deconvolution, Backpropagation, Guided Backpropagation, and Integrated Gradients. Check out [grad.py](https://github.com/1202kbs/Understanding-NN/blob/master/models/grad.py), a modular implementation of various gradient-based visualization techniques. +In this section, we explore various types of gradient-based visualization methods such as Deconvolution, Backpropagation, Guided Backpropagation, Integrated Gradients and SmoothGrad. Check out [grad.py](https://github.com/1202kbs/Understanding-NN/blob/master/models/grad.py), a modular implementation of various gradient-based visualization techniques. ### 3.1 Deconvolution