fredhohman / summitLinks
🏔️ Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
☆116Updated 6 years ago
Alternatives and similar repositories for summit
Users that are interested in summit are comparing it to the libraries listed below
Sorting:
- Towards Automatic Concept-based Explanations☆162Updated last year
- ☆113Updated 3 years ago
- ☆51Updated 5 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Code for the TCAV ML interpretability project☆650Updated this week
- ☆135Updated 6 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- Visualizing memorization in RNNs☆66Updated 5 years ago
- Python package for creating rule-based explanations for classifiers.☆60Updated 6 years ago
- Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural N…☆306Updated 5 years ago
- Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers☆98Updated 7 years ago
- Tools for training explainable models using attribution priors.☆125Updated 4 years ago
- To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…☆178Updated 2 years ago
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆54Updated 3 years ago
- The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…☆335Updated 3 years ago
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆62Updated 6 years ago
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 7 years ago
- REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets --- https://arxiv.org/abs/2004.07999☆110Updated 3 years ago
- Code/figures in Right for the Right Reasons☆57Updated 5 years ago
- Estimating Example Difficulty using Variance of Gradients☆64Updated 3 years ago
- 🛠️ Corrected Test Sets for ImageNet, MNIST, CIFAR, Caltech-256, QuickDraw, IMDB, Amazon Reviews, 20News, and AudioSet☆186Updated last month
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- PyTorch implementation of parity loss as constraints function to realize the fairness of machine learning.☆73Updated 2 years ago
- PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation☆338Updated 4 years ago
- This repository is all about papers and tools of Explainable AI☆36Updated 6 years ago
- Quantitative Testing with Concept Activation Vectors in PyTorch☆43Updated 6 years ago
- Full-gradient saliency maps☆212Updated 2 years ago
- Calibration of Convolutional Neural Networks☆171Updated 2 years ago
- ☆122Updated 3 years ago
- Papers on interpretable deep learning, for review☆29Updated 8 years ago