List of papers in the area of Explainable Artificial Intelligence Year wise
2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps pdf
Visualizing and understanding convolutional networks pdf
Object detectors emerge in deep scene CNN’s pdf
2015
Understanding Neural Network through Deep Visualization pdf
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation pdf
Understanding Deep Image Representation by Inverting Them pdf
Striving for Simplicity: The All Convolutional Net pdf
2016
An unexpected unity among methods for interpreting model predictions pdf
“Why Should I Trust you?” Explaining the Predictions of Any Classifier pdf
Learning deep features for discriminative localization pdf
2017
SmoothGrad: Removing Noise By Adding Noise pdf
Axiomatic Attribution for Deep Neural Networks pdf
Learning Important Features Through Propagating Activation Differences pdf
Understanding Black-box Predictions via Influence Functions pdf
Interpretable Explanations of Black Boxes by Meaningful Perturbation pdf
Visualizing deep neural network decisions: Prediction difference analysis pdf
Network Dissection: Quantifying Interpretability of Deep Visual Representations pdf
The (Un)reliability of Saliency Methods pdf
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations pdf
Understanding intermediate layers using linear classifier probes pdf
Using KL-divergence to focus Deep Visual Explanation pdf
A Unified Approach to Interpreting Model Predictions pdf
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization pdf
2018
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions pdf
Towards Robust Interpretability with Self-Explaining Neural Networks pdf
Towards Better Understanding of Gradient-Based Attribution Methods For Deep Neural Networks pdf
Interpretable Convolutional Neural Networks pdf
Grad-cam++: Improved Visual Explanations for Deep Convolutional Networks pdf
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in deep Neural Networks pdf
Sanity Checks for Saliency Maps pdf
Imagenet trained CNN’s are biased towards texture, increasing shape bias improves accuracy and robustness pdf
Anchors: High precision model agnostic explanations pdf
2019
A Simple Saliency Method That Passes the Sanity Check pdf
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation pdf
Counterfactual Visual Explanations pdf
Explainable AI for Trees: From Local Explanations to Global Understanding pdf
Why did you do that?: Explaining black-box models with inductive synthesis pdf
TED: Teaching AI to explain its decisions pdf
This Looks Like That: Deep Learning for Interpretable Image Recognition pdf
Interpretable Image Recognition with Hierarchical Prototypes pdf
Understanding Deep Neural Networks For Regression In Leaf Counting pdf
Score-CAM: Improved Visual Explanations Via Score-Weighted Class Activation Mapping pdf
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space pdf
Learning Reliable Visual Saliency for Model Explanations pdf
2020
Explanation by Progressive Exaggeration pdf
Workshops
https://xai.kdd2019.a.intuit.com/
https://human-centered.ai/methods-of-explainable-ai/
https://sites.google.com/view/xai2019/home
http://www.heatmapping.org/ ( contains a list of workshops )