M-Nauta / Explaining_Prototypes
This repository contains code for explaining prototypes learned by ProtoPNet, by quantifying the influence of color hue, shape, texture, contrast and saturation in a prototype
☆13Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for Explaining_Prototypes
- GitHub repository for KDD 2021 work: ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classificati…☆11Updated 3 years ago
- ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition☆34Updated last year
- The official repository for Deformable ProtoPNet, as described in "Deformable ProtoPNet: An Interpretable Image Classifier Using Deformab…☆37Updated 4 months ago
- PyTorch Transformer-based Language Model Implementation of ConceptSHAP☆12Updated 4 years ago
- Generalizing to unseen domains via distribution matching☆70Updated 4 years ago
- ☆16Updated 4 years ago
- [ICCV 2023] Evaluation and Improvement of Interpretability for Self-Explainable Part-Prototype Networks☆13Updated last year
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 3 years ago
- ☆35Updated 3 years ago
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆51Updated 2 years ago
- ☆10Updated 3 years ago
- Improving the Fairness of Chest X-ray Classifiers☆14Updated 2 years ago
- ICCV2021 paper: Interpretable Image Recognition by Constructing Transparent Embedding Space (TesNet)☆19Updated 2 years ago
- ☆11Updated 2 years ago
- [ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging☆59Updated last year
- ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping☆54Updated 2 years ago
- ☆46Updated 4 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 3 years ago
- Code for the ICLR 2022 paper "Attention-based interpretability with Concept Transformers"☆39Updated last year
- ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021☆90Updated 2 years ago
- Quantile risk minimization☆24Updated 3 months ago
- ☆72Updated 4 years ago
- Official repository for the AAAI-21 paper 'Explainable Models with Consistent Interpretations'☆18Updated 2 years ago
- A Generic Multi-classifier Paradigm forIncremental Learning☆11Updated 4 years ago
- ☆41Updated last year
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 2 years ago
- HIVE: Evaluating the Human Interpretability of Visual Explanations (ECCV 2022)☆19Updated last year
- [CVPR 2022] HINT: Hierarchical Neuron Concept Explainer☆21Updated last year
- NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information☆32Updated 2 years ago