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1. A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)

   Python 759 135

2. MineTime public repository for issue tracking

   340 12

3. Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)

   Python 61 13

4. Feedforward implementation of Lightweight Probabilistic Deep Networks for Keras and Tensorflow

   Jupyter Notebook 14 4

5. EWS API for TypeScript/JavaScript - ported from OfficeDev/ews-managed-api - node, cordova, meteor, Ionic, Electron, Outlook Add-Ins

   TypeScript 292 76

6. On-the-fly Structured Pruning for PyTorch models. This library implements several attributions metrics and structured pruning utils for neural networks in PyTorch.

   Jupyter Notebook 168 21