论文标题
Xplique：深度学习解释性工具箱
Xplique: A Deep Learning Explainability Toolbox
论文作者
论文摘要
当今最先进的机器学习型号几乎无法审查。解释性方法的主要挑战是通过揭示导致给定决定的策略，通过表征其内部状态或研究基础数据表示的策略来帮助研究人员开放这些黑匣子。为了应对这一挑战，我们已经开发了Xplique：一种用于解释性的软件库，其中包括代表性的解释性方法以及相关的评估指标。它与最受欢迎的学习库之一相结合：Tensorflow以及其他图书馆，包括Pytorch，Scikit-Learn和Theano。该代码是根据MIT许可证获得许可的，可在Github.com/deel-ai/xplique中免费获得。
Today's most advanced machine-learning models are hardly scrutable. The key challenge for explainability methods is to help assisting researchers in opening up these black boxes, by revealing the strategy that led to a given decision, by characterizing their internal states or by studying the underlying data representation. To address this challenge, we have developed Xplique: a software library for explainability which includes representative explainability methods as well as associated evaluation metrics. It interfaces with one of the most popular learning libraries: Tensorflow as well as other libraries including PyTorch, scikit-learn and Theano. The code is licensed under the MIT license and is freely available at github.com/deel-ai/xplique.
