mlsanityData to 7 Oct 2026

PyTorch, Explain! A Python library for Logic Explained Networks

arXiv 2105.11697 ↗First posted 25 May 2021cs.LG cs.AIcited by 5

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Abstract (arXiv)

"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.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 5 of its 22 references that are in the map. First posted on arXiv 25 May 2021.

Builds on

5 of 22 references.

References · 5

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2020Concept Bottleneck Modelscited by 1,022
  3. 2020Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Surveycited by 252
  4. 2020Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claimscited by 163
  5. 2020Now You See Me (CME): Concept-based Model Extractioncited by 51

Built on by

Cited by year

Citing papers per year: 2021: 3; 2022: 1; 2023: 0; 2024: 0; 2025: 1.

5 papers.