rachtibat / zennit-crpLinks
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
☆140Updated 2 weeks ago
Alternatives and similar repositories for zennit-crp
Users that are interested in zennit-crp are comparing it to the libraries listed below
Sorting:
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆239Updated 5 months ago
- A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.☆102Updated 3 years ago
- Dataset and code for the CLEVR-XAI dataset.☆33Updated 2 years ago
- LENS Project☆52Updated last year
- Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.☆15Updated 2 years ago
- MetaQuantus is an XAI performance tool to identify reliable evaluation metrics☆40Updated last year
- Papers and code of Explainable AI esp. w.r.t. Image classificiation☆226Updated 3 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models", our NeurIPS 2023 paper "Learning to Receive Help", and our ICML 2025 pa…☆72Updated this week
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆636Updated last week
- Mechanistic understanding and validation of large AI models with SemanticLens☆50Updated last month
- Layer-wise Relevance Propagation for Large Language Models and Vision Transformers [ICML 2024]☆218Updated 6 months ago
- 👋 Aligning Human & Machine Vision using explainability☆54Updated 2 years ago
- 👋 Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)☆71Updated 2 years ago
- Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.☆20Updated 2 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆252Updated last year
- ☆122Updated 3 years ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆139Updated 4 years ago
- Official PyTorch implementation of improved B-cos models☆55Updated last month
- 👋 Overcomplete is a Vision-based SAE Toolbox☆117Updated last month
- Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023☆89Updated last year
- Concept Bottleneck Models, ICML 2020☆237Updated 2 years ago
- PyTorch Explain: Interpretable Deep Learning in Python.☆168Updated last year
- [ICLR 23] A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled c…☆129Updated last year
- A toolkit for quantitative evaluation of data attribution methods.☆54Updated 6 months ago
- [NeurIPS 2024] CoSy is an automatic evaluation framework for textual explanations of neurons.☆19Updated this week
- Basic LRP implementation in PyTorch☆174Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆164Updated 3 years ago
- Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.☆55Updated last year
- 👋 Xplique is a Neural Networks Explainability Toolbox☆728Updated last week
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆26Updated last year