evidential-deep-learning:使用神经网络学习快速,可扩展且经过校准的不确定性度量!

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证据深度学习 “所有模型都是错误的,但是某些模型(知道何时可以信任它们)是有用的!” -乔治·博克斯(改编) 该存储库包含用于重现的代码(如所发布的),以及更通用的代码,以利用证据学习来训练神经网络,以直接从数据中学习不确定性! 设置 要使用此软件包,必须首先安装以下依赖项: python(> = 3.7) 张量流(> = 2.0) pytorch(支持即将推出) 现在,您可以安装以开始为模型添加证据层和损失! pip install evidential-deep-learning 现在,您可以直接在现有tf.keras模型管道( Sequential , Functional或model-subclassing )的一部分中直接使用此包: >>> import evidential_deep_learning as edl 例子 要使用证据深度学习,必须将模型的最后

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