pyc-team / pytorch_conceptsLinks
PyC (Pytorch Concepts) is a PyTorch-based library for training concept-based interpretable deep learning models.
☆29Updated this week
Alternatives and similar repositories for pytorch_concepts
Users that are interested in pytorch_concepts are comparing it to the libraries listed below
Sorting:
- PyTorch Explain: Interpretable Deep Learning in Python.☆169Updated last year
- Concept Bottleneck Models, ICML 2020☆239Updated 2 years ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization☆140Updated 3 weeks ago
- Dataset and code for the CLEVR-XAI dataset.☆33Updated 2 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models", our NeurIPS 2023 paper "Learning to Receive Help", and our ICML 2025 pa…☆73Updated 2 weeks ago
- Optimal Transport Dataset Distance☆174Updated 3 years ago
- A repository for summaries of recent explainable AI/Interpretable ML approaches☆88Updated last year
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆100Updated last year
- Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023☆89Updated last year
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆252Updated last year
- Mechanistic understanding and validation of large AI models with SemanticLens☆50Updated 2 months ago
- CausalPFN: Amortized Causal Effect Estimation via In-Context Learning☆88Updated 2 months ago
- ☆34Updated last year
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆77Updated 3 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆55Updated 3 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆70Updated 3 years ago
- Conformal Language Modeling☆31Updated 2 years ago
- ☆26Updated 2 years ago
- A toolkit for quantitative evaluation of data attribution methods.☆55Updated 6 months ago
- Model Zoos published at the NeurIPS 2022 Dataset & Benchmark track: "Model Zoos: A Dataset of Diverse Populations of Neural Network Model…☆57Updated 4 months ago
- Layer-wise Relevance Propagation for Large Language Models and Vision Transformers [ICML 2024]☆219Updated 6 months ago
- PyTorch implementation of Logic Tensor Networks, a Neural-Symbolic framework.☆148Updated last year
- List of ML conferences with important dates and accepted paper list☆208Updated last month
- a python framework to build, learn and reason about probabilistic circuits and tensor networks☆133Updated last week
- 👋 Overcomplete is a Vision-based SAE Toolbox☆119Updated 2 months ago
- ☆116Updated 11 months ago
- A fast, effective data attribution method for neural networks in PyTorch☆229Updated last year
- Influence Analysis and Estimation - Survey, Papers, and Taxonomy☆86Updated last year
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago