dais-ita / interpretability-papersLinks
Papers on interpretable deep learning, for review
☆29Updated 7 years ago
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- Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"☆31Updated 6 years ago
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- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
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- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
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- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)☆141Updated 6 years ago
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- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆62Updated 6 years ago
- Code to reproduce some of the figures in the paper "On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima"☆145Updated 8 years ago
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