# Explaining decision of model from its prediction

arXiv: https://arxiv.org/abs/2106.08366 · HTML: https://mlsanity.com/paper/2106.08366/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 7 references that are in the map.
- First posted on arXiv 15 Jun 2021.

## Builds on (most cited first, 4 of 4)

- [Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://mlsanity.com/paper/1610.02391/) (2016)
- [Understanding Neural Networks Through Deep Visualization](https://mlsanity.com/paper/1506.06579/) (2015)
- [Breast Cancer Histopathology Image Classification and Localization using Multiple Instance Learning](https://mlsanity.com/paper/2003.00823/) (2020)
- [Saliency-driven Class Impressions for Feature Visualization of Deep Neural Networks](https://mlsanity.com/paper/2007.15861/) (2020)

## Abstract (arXiv)

This document summarizes different visual explanations methods such as CAM, Grad-CAM, Localization using Multiple Instance Learning - Saliency-based methods, Saliency-driven Class-Impressions, Muting pixels in input image - Adversarial methods and Activation visualization, Convolution filter visualization - Feature-based methods. We have also shown the results produced by different methods and a comparison between CAM, GradCAM, and Guided Backpropagation.