maxdreyer / L-CRP
Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.
☆11Updated 9 months ago
Related projects ⓘ
Alternatives and complementary repositories for L-CRP
- Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.☆19Updated 9 months ago
- Invertible Concept-based Explanation (ICE)☆18Updated 3 years ago
- Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers, Paper accepted at eXCV workshop of ECCV 2…☆14Updated 2 weeks ago
- Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023☆72Updated 5 months ago
- Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"☆44Updated 3 months ago
- Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curv…☆13Updated 2 years ago
- Official PyTorch implementation of improved B-cos models☆42Updated 8 months ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization☆118Updated 5 months ago
- Implementation of Concept-level Debugging of Part-Prototype Networks☆11Updated last year
- Code and data for the paper "In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation"☆24Updated last year
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆99Updated last year
- Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.☆28Updated last week
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Updated 2 years ago
- This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human con…☆9Updated 2 years ago
- ICLR 2024: Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations☆15Updated 7 months ago
- A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled concept dat…☆79Updated 7 months ago
- Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet☆29Updated last year
- ☆35Updated 6 months ago
- 👋 Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)☆56Updated last year
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆51Updated 2 years ago
- PyTorch Transformer-based Language Model Implementation of ConceptSHAP☆12Updated 4 years ago
- [ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging☆59Updated last year
- Prototypical Concept-based Explanations, accepted at SAIAD workshop at CVPR 2024.☆9Updated 4 months ago
- A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.☆78Updated 2 years ago
- Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…☆13Updated last year
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…☆52Updated this week
- Learning Bottleneck Concepts in Image Classification (CVPR 2023)☆34Updated last year
- Code for the paper "Explain Any Concept: Segment Anything Meets Concept-Based Explanation". Poster @ NeurIPS 2023☆40Updated 11 months ago
- Implementation of the paper "A Framework for Learning Ante-hoc Explainable Models via Concepts" (CVPR 2022).☆8Updated 3 months ago
- Test-Time Adaptation via Conjugate Pseudo-Labels☆38Updated last year