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@ -34,12 +34,12 @@ This is an on-going attempt to consolidate interesting efforts in the area of un
### Real images / Segmentation Masks
* Object Detectors Emerge in Deep Scene CNNs. Zhou et al. 2015 [pdf](https://arxiv.org/abs/1412.6856)
* Network Dissection: Quantifying Interpretability of Deep Visual Representations. Bau et al. 2017 [url](http://netdissect.csail.mit.edu/) | [pdf](http://netdissect.csail.mit.edu/final-network-dissection.pdf)
* Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks. Fong & Vedaldi 2018 [pdf](https://arxiv.org/abs/1801.03454)
* Network Dissection: Quantifying Interpretability of Deep Visual Representations. _Bau et al. 2017_ [url](http://netdissect.csail.mit.edu/) | [pdf](http://netdissect.csail.mit.edu/final-network-dissection.pdf)
* GAN Dissection: Visualizing and Understanding Generative Adversarial Networks. _Bau et al. 2018_ [pdf](https://arxiv.org/abs/1811.10597)
* Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks. _Fong & Vedaldi 2018_ [pdf](https://arxiv.org/abs/1801.03454)
# Heatmaps / Attribution
### White-box
* Learning how to explain neural networks: PatternNet and PatternAttribution [pdf](https://arxiv.org/abs/1705.05598)
* A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations. _Nie et al. 2018_ [pdf](https://arxiv.org/abs/1805.07039)
* A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks [pdf](https://arxiv.org/pdf/1606.07757.pdf)
* CAM: Learning Deep Features for Discriminative Localization. _Zhou et al. 2016_ [code](https://github.com/metalbubble/CAM) | [web](http://cnnlocalization.csail.mit.edu/)
@ -72,6 +72,7 @@ This is an on-going attempt to consolidate interesting efforts in the area of un
* Improving the Interpretability of Deep Neural Networks with Knowledge Distillation. _Liu et al. 2018_ [pdf](https://arxiv.org/pdf/1812.10924.pdf)
# Learning to explain
* Learning how to explain neural networks: PatternNet and PatternAttribution [pdf](https://arxiv.org/abs/1705.05598)
* Deep Learning for Case-Based Reasoning through Prototypes [pdf](https://arxiv.org/pdf/1710.04806.pdf)
* Unsupervised Learning of Neural Networks to Explain Neural Networks [pdf](https://arxiv.org/abs/1805.07468)