dais-ita / interpretability-papersLinks
Papers on interpretable deep learning, for review
β29Updated 8 years ago
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- Code for "Testing Robustness Against Unforeseen Adversaries"β80Updated last year
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" π§ (ICLR 2019)β129Updated 4 years ago
- Release of CIFAR-10.1, a new test set for CIFAR-10.β225Updated 5 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]β31Updated 5 years ago
- Example code for the paper "Understanding deep learning requires rethinking generalization"β178Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" htβ¦β128Updated 4 years ago
- Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"β32Updated 6 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893β91Updated 5 years ago
- SmoothGrad implementation in PyTorchβ172Updated 4 years ago
- Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019β14Updated last year
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).β51Updated 5 years ago
- Original dataset release for CIFAR-10Hβ83Updated 5 years ago
- Geometric Certifications of Neural Netsβ42Updated 3 years ago
- Learning perturbation sets for robust machine learningβ65Updated 4 years ago
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)β101Updated 3 years ago
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- Adversarially Robust Neural Network on MNIST.β63Updated 4 years ago
- Interpretation of Neural Network is Fragileβ36Updated last year
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- Explaining Image Classifiers by Counterfactual Generationβ28Updated 3 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)β62Updated 2 years ago
- Computing various norms/measures on over-parametrized neural networksβ50Updated 7 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'β62Updated 7 years ago
- A drop-in replacement for CIFAR-10.β247Updated 4 years ago
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- A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturbβ¦β12Updated 5 years ago
- Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"β164Updated 5 years ago
- Data, code & materials from the paper "Generalisation in humans and deep neural networks" (NeurIPS 2018)β95Updated 2 years ago
- Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)β142Updated 6 years ago