rachtibat / zennit-crpLinks
An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization
☆137Updated last year
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.☆233Updated 3 months ago
- A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.☆98Updated 3 years ago
- Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.☆15Updated last year
- MetaQuantus is an XAI performance tool to identify reliable evaluation metrics☆39Updated last year
- LENS Project☆51Updated last year
- Dataset and code for the CLEVR-XAI dataset.☆32Updated 2 years ago
- Papers and code of Explainable AI esp. w.r.t. Image classificiation☆223Updated 3 years ago
- Layer-wise Relevance Propagation for Large Language Models and Vision Transformers [ICML 2024]☆202Updated 4 months ago
- Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.☆20Updated last year
- Repository for our NeurIPS 2022 paper "Concept Embedding Models", our NeurIPS 2023 paper "Learning to Receive Help", and our ICML 2025 pa…☆69Updated last month
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆628Updated 3 months ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆139Updated 4 years ago
- 👋 Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)☆70Updated 2 years ago
- Mechanistic understanding and validation of large AI models with SemanticLens☆46Updated last month
- Official PyTorch implementation of improved B-cos models☆54Updated last month
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆248Updated last year
- [NeurIPS 2024] CoSy is an automatic evaluation framework for textual explanations of neurons.☆18Updated 4 months ago
- ☆122Updated 3 years ago
- 👋 Overcomplete is a Vision-based SAE Toolbox☆101Updated last week
- Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023☆86Updated last year
- Concept Bottleneck Models, ICML 2020☆223Updated 2 years ago
- Basic LRP implementation in PyTorch☆172Updated last year
- A toolkit for quantitative evaluation of data attribution methods.☆53Updated 4 months ago
- [ICLR 23] A new framework to transform any neural networks into an interpretable concept-bottleneck-model (CBM) without needing labeled c…☆120Updated last year
- Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.☆49Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆160Updated 3 years ago
- 👋 Aligning Human & Machine Vision using explainability☆53Updated 2 years ago
- implements some LRP rules to get explanations for Resnets and Densenet-121, including batchnorm-Conv canonization and tensorbiased layers…☆25Updated last year
- ☆41Updated last year
- Pytorch implementation of various neural network interpretability methods☆118Updated 3 years ago