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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 491 93

  2. MineTime public repository for issue tracking

    347 8

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

    Python 29 8

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

    Jupyter Notebook 6 4

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

    TypeScript 233 55

  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 15 3

792 contributions in the last year

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Contribution activity

December 1, 2020

7 contributions in private repositories Dec 1

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