- Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
- Interpretable machine learning
- AI Explainability Whitepaper by google
- Limitations of Interpretable Machine Learning Methods
- Explainable ML by [Hung-yi Lee]
- AAAI 2020 Tutorial
- Faster Data Science Education from kaggle
- Interpretability and Explainability in Machine Learning COMPSCI 282BR, Harvard University
- 详解深度学习的可解释性研究（上篇）
- Guide to Interpretable Machine Learning by Matthew Stewart
- interpretability cheat-sheet
- How to Explain the Prediction of a Machine Learning Model?
- XAI—Explainable artificial intelligence
- Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
- Interpretable data visualizations for understanding how texts differ at the word level
- Discovering Interpretable GAN This work gave a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis, such as change of viewpoint, aging, lighting, and time of day.
- Model interpretability and understanding for PyTorch Captum is a model interpretability and understanding library for PyTorch.