oneTaken/awesome_deep_learning_interpretability
A curated collection of high-citation research papers on deep learning model interpretability and explainability from top ML/CV conferences.
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This repository collects academic papers on neural network interpretability, organized by publication venue and citation count. It covers explainability methods for deep learning models including convolutional networks and NLP models. The collection spans top-tier venues like CVPR, ICLR, NeurIPS, and includes links to implementations where available.
Frequently asked
- What is oneTaken/awesome_deep_learning_interpretability?
- A curated collection of high-citation research papers on deep learning model interpretability and explainability from top ML/CV conferences.
- Is awesome_deep_learning_interpretability open source?
- Yes — oneTaken/awesome_deep_learning_interpretability is open source, released under the MIT license.
- How popular is awesome_deep_learning_interpretability?
- oneTaken/awesome_deep_learning_interpretability has 767 stars on GitHub.
- Where can I find awesome_deep_learning_interpretability?
- oneTaken/awesome_deep_learning_interpretability is on GitHub at https://github.com/oneTaken/awesome_deep_learning_interpretability.