From 4b5f57ea6d4926b85aaf0417ad259b4e93fff4ca Mon Sep 17 00:00:00 2001 From: Behrooz Date: Fri, 8 Feb 2019 16:04:08 -0500 Subject: [PATCH] add new methods --- README.md | 4 ++-- interpretability_in_medicine.md | 2 +- interpretability_in_smart_cities.md | 2 +- interpretability_methods.md | 13 ++++++++++--- 4 files changed, 14 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 8197393..5437e99 100644 --- a/README.md +++ b/README.md @@ -27,12 +27,12 @@ Here I try to organize most important ideas in the field of interpretable machin - [Electronic Health Records](./interpretability_in_medicine.md) - [Radiology Reports](./interpretability_in_medicine.md) -[Applications of Interpretability in Smart Cities](./interpretability_applications.md) +[Applications of Interpretability in Smart Cities](./interpretability_in_smart_cities.md) ------------------------------------------------------------------------------- - [Self Driving Cars](./interpretability_applications.md#self-driving-cars) -[Tools of Interpretability in Practice](./interpretability_methods.md) +[Tools for Interpretability in Practice](./interpretability_methods.md) ------------------------------------------------------------------------------- - [What-If](https://pair-code.github.io/what-if-tool/) diff --git a/interpretability_in_medicine.md b/interpretability_in_medicine.md index 760e5f5..daa9a57 100644 --- a/interpretability_in_medicine.md +++ b/interpretability_in_medicine.md @@ -1,4 +1,4 @@ -Interpretability in Medicine +Interpretability Applications in Medicine =============================================================================== Intracranial Hemorrhage diff --git a/interpretability_in_smart_cities.md b/interpretability_in_smart_cities.md index 675077a..e44e262 100644 --- a/interpretability_in_smart_cities.md +++ b/interpretability_in_smart_cities.md @@ -1,4 +1,4 @@ -Interpretability Applications +Interpretability Applications in Smart Cities =============================================================================== Self Driving Cars diff --git a/interpretability_methods.md b/interpretability_methods.md index b3881cc..fc443ab 100644 --- a/interpretability_methods.md +++ b/interpretability_methods.md @@ -16,9 +16,14 @@ Decomposition-based Methods Gradient-based Methods ------------------------------------------------------------------------------- -- **Class Activation Map (CAM)** : Learning Deep Features for Discriminative Localization’. \[[paper](http://dx.doi.org/10.1109/CVPR.2016.319)] -- **Grad-CAM**: Selvaraju, R. R. et al.(2017) ‘Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization’. \[[paper](http://dx.doi.org/10.1109/ICCV.2017.74)] -- **Grad-CAM++**: building on Grad-CAM, it provides better visual explanations of CNN model predictions, in terms of better object localization as well as explaining occurrences of multiple object instances in a single image. \[[paper](https://arxiv.org/abs/1710.11063)] +- **Class Activation Map (CAM)** : Learning Deep Features for Discriminative Localization. \[[paper](http://dx.doi.org/10.1109/CVPR.2016.319)] +- **Grad-CAM**: Visual Explanations from Deep Networks via Gradient-Based Localization. \[[paper](http://dx.doi.org/10.1109/ICCV.2017.74)] +- **Grad-CAM++**: Building on Grad-CAM, it provides better visual explanations of CNN model predictions, in terms of better object localization as well as explaining occurrences of multiple object instances in a single image. \[[paper](https://arxiv.org/abs/1710.11063)] +- **SmoothGrad**: removing noise by adding noise \[[paper](https://arxiv.org/abs/1706.03825)] \[[code](https://github.com/pair-code/saliency)] \[[more descriptions](https://pair-code.github.io/saliency/)] + +- **Integrated Gradients**: Axiomatic Attribution for Deep Networks. It uses to two fundamental axioms *Sensitivity* and *Implementation Invariance* to guide the design of a new attribution method. \[[paper](https://arxiv.org/abs/1703.01365)] \[[code](https://github.com/ankurtaly/Integrated-Gradients)] + +- Vanilla Gradients (paper, paper) Representation Visualization and Quantification ------------------------------------------------------------------------------- @@ -29,6 +34,8 @@ Representation Visualization and Quantification - Striving for Simplicity: The All Convolutional Net (2014). \[[paper](https://arxiv.org/abs/1412.6806)] +- Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps (2013). \[[paper](https://arxiv.org/abs/1312.6034)] + Others -----------