PyTorch, Explain! A Python library for Logic Explained Networks
arXiv:2105.11697
Abstract
"PyTorch, Explain!" is a Python module integrating a variety of state-of-the-art approaches to provide logic explanations from neural networks. This package focuses on bringing these methods to non-specialists. It has minimal dependencies and it is distributed under the Apache 2.0 licence allowing both academic and commercial use. Source code and documentation can be downloaded from the github repository: https://github.com/pietrobarbiero/pytorch_explain.
References in corpus (7)
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey
- Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
- Concept Bottleneck Models
- Towards Automatic Concept-based Explanations
- Entropy-based Logic Explanations of Neural Networks
- Now You See Me (CME): Concept-based Model Extraction