osu-xai / pytorch-saliencyLinks
Pytorch plugin to generate saliency maps for neural networks
☆12Updated 6 years ago
Alternatives and similar repositories for pytorch-saliency
Users that are interested in pytorch-saliency are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of Real Time Image Saliency for Black Box Classifiers https://arxiv.org/abs/1705.07857☆59Updated 5 years ago
- Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"☆128Updated 5 years ago
- SmoothGrad implementation in PyTorch☆171Updated 4 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"☆31Updated 5 years ago
- Code for Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks☆30Updated 7 years ago
- Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"☆161Updated 5 years ago
- Visualizing how deep networks make decisions☆66Updated 6 years ago
- Real-time image saliency 🌠 (NIPS 2017)☆125Updated 7 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Data, code & materials from the paper "Generalisation in humans and deep neural networks" (NeurIPS 2018)☆96Updated last year
- Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights☆182Updated 6 years ago
- Official repository for "Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps".☆34Updated 5 years ago
- Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning☆94Updated 5 years ago
- [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data☆111Updated 5 years ago
- ☆141Updated 4 years ago
- Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image cor…☆61Updated 2 years ago
- ☆66Updated 6 years ago
- Pytorch Implementation of recent visual attribution methods for model interpretability☆146Updated 5 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆35Updated 7 years ago
- Principled Detection of Out-of-Distribution Examples in Neural Networks☆202Updated 8 years ago
- Self-Supervised Representation Learning by Rotation Feature Decoupling☆95Updated 6 years ago
- ☆26Updated 5 years ago
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Quantitative Testing with Concept Activation Vectors in PyTorch☆42Updated 6 years ago
- ☆34Updated 7 years ago
- A PyTorch implementation of shake-shake☆111Updated 5 years ago
- Visualizing Deep Networks by Optimizing with Integrated Gradients (I-GOS)☆36Updated 2 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆32Updated 5 years ago
- Official repository for "Bridging Adversarial Robustness and Gradient Interpretability".☆30Updated 6 years ago