Detect model's attention
☆172Jul 2, 2020Updated 5 years ago
Alternatives and similar repositories for RISE
Users that are interested in RISE are comparing it to the libraries listed below
Sorting:
- A PyTorch implementation of D-RISE☆38Jun 26, 2021Updated 4 years ago
- HIVE: Evaluating the Human Interpretability of Visual Explanations (ECCV 2022)☆22Jan 19, 2023Updated 3 years ago
- PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation☆337Nov 30, 2021Updated 4 years ago
- Explanation Optimization☆13Oct 16, 2020Updated 5 years ago
- High resolution XAI method for convolutional neural networks☆23Apr 26, 2023Updated 2 years ago
- ☆113Nov 21, 2022Updated 3 years ago
- Implementation of "MULE: Multimodal Universal Language Embedding"☆16Dec 23, 2019Updated 6 years ago
- ☆20Jul 30, 2024Updated last year
- Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…☆25Feb 23, 2022Updated 4 years ago
- Official implementation of Score-CAM in PyTorch☆434Aug 6, 2022Updated 3 years ago
- Understanding Deep Networks via Extremal Perturbations and Smooth Masks☆349Jul 22, 2020Updated 5 years ago
- Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).☆994Mar 20, 2024Updated 2 years ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆139Feb 19, 2021Updated 5 years ago
- Guidelines for the responsible use of explainable AI and machine learning.☆17Jan 30, 2023Updated 3 years ago
- Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"☆32Sep 25, 2019Updated 6 years ago
- The official code for our TIP paper 'LayerCAM: Exploring Hierarchical Class Activation Maps for Localization'☆131Mar 19, 2022Updated 4 years ago
- [XAI4CV CVPR 2023] Towards Evaluating Explanations of Vision Transformers for Medical Imaging☆10Dec 1, 2023Updated 2 years ago
- Papers and code of Explainable AI esp. w.r.t. Image classificiation☆226Jun 28, 2022Updated 3 years ago
- ☆29Oct 24, 2023Updated 2 years ago
- Official repository of the paper "Explainable Deep Learning Methods in Medical Image Classification: A Survey", ACM Computing Surveys (CS…☆10Jan 9, 2024Updated 2 years ago
- A toolbox to iNNvestigate neural networks' predictions!☆1,307Apr 11, 2025Updated 11 months ago
- ☆14Apr 23, 2019Updated 6 years ago
- Local explanations with uncertainty 💐!☆42Aug 8, 2023Updated 2 years ago
- Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, I…☆12,701Apr 7, 2025Updated 11 months ago
- Full-gradient saliency maps☆212Feb 25, 2023Updated 3 years ago
- ☆20Jan 23, 2020Updated 6 years ago
- There and Back Again: Revisiting Backpropagation Saliency Methods (CVPR 2020)☆53Apr 7, 2020Updated 5 years ago
- A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.☆10Jul 28, 2023Updated 2 years ago
- Repository for the paper "Benchmarking and Survey of Explanation Methods for Black Box Models"☆18Jun 28, 2022Updated 3 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆647Mar 9, 2026Updated last week
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆26Mar 7, 2024Updated 2 years ago
- Making high-accuracy and visually-interpretable decision tree-based models for semantic segmentation http://segnbdt.aaalv.in☆11Oct 12, 2021Updated 4 years ago
- A generalized gradient-based CNN visualization technique☆297Apr 17, 2019Updated 6 years ago
- Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?☆41Aug 19, 2022Updated 3 years ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆241Jan 30, 2026Updated last month
- ☆13Nov 29, 2021Updated 4 years ago
- This project uses the Labeled Faces in the Wild (LFW) dataset, and the goal is to train variants of deep architectures to learn when a…☆19Sep 14, 2018Updated 7 years ago
- The official implementation of "A2XP: Towards Private Domain Generalization".☆14Jun 14, 2024Updated last year
- Model interpretability and understanding for PyTorch☆5,580Mar 11, 2026Updated last week