Shypd.aiThe largest open index of AI toolsevidential-deep-learning is an Open Source & Models tool that enables neural networks to learn measures of uncertainty directly from data. It provides code for Deep Evidential Regression and supports fast, scalable, and calibrated uncertainty measures.
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evidential-deep-learning is an open-source Python package designed to help neural networks learn their own measures of uncertainty directly from data. It provides the necessary code to reproduce the Deep Evidential Regression paper published in NeurIPS 2020, offering a general framework for evidential learning. The tool allows users to integrate evidential layers and loss functions into existing `tf.keras` model pipelines, supporting both fully connected and convolutional layers. This enables the development of models that can provide fast, scalable, and calibrated measures of uncertainty, enhancing their trustworthiness and utility. The package is compatible with Python (>=3.7) and TensorFlow (>=2.0), with PyTorch support planned.
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