pnxenopoulos / cav-keras
Concept activation vectors for Keras
☆13Updated 2 years ago
Alternatives and similar repositories for cav-keras:
Users that are interested in cav-keras are comparing it to the libraries listed below
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆53Updated 3 years ago
- 'Robust Semantic Interpretability: Revisiting Concept Activation Vectors' Official Implementation☆11Updated 4 years ago
- PyTorch Transformer-based Language Model Implementation of ConceptSHAP☆14Updated 4 years ago
- Towards Automatic Concept-based Explanations☆159Updated 11 months ago
- Official PyTorch implementation for our ICCV 2019 paper - Fooling Network Interpretation in Image Classification☆24Updated 5 years ago
- ☆46Updated 4 years ago
- ☆92Updated 4 years ago
- ☆51Updated 4 years ago
- Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…☆25Updated 3 years ago
- Pytorch implementation of "A Simple Framework for Contrastive Learning of Visual Representations"☆82Updated 11 months ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- Explaining Image Classifiers by Counterfactual Generation☆28Updated 2 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆59Updated 5 years ago
- A list of papers on Active Learning and Uncertainty Estimation for Neural Networks.☆66Updated 4 years ago
- Quantitative Testing with Concept Activation Vectors in PyTorch☆42Updated 6 years ago
- PyTorch Implementation of CVPR'19 (oral) - Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach☆27Updated 5 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆129Updated 3 years ago
- IBD: Interpretable Basis Decomposition for Visual Explanation☆52Updated 6 years ago
- Code example for the paper, "Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robust…☆23Updated last year
- An implementation of the Residual Flow algorithm for out-of-distribution detection.☆30Updated 2 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- ☆17Updated 4 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 3 years ago
- CME: Concept-based Model Extraction☆12Updated 4 years ago
- Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks☆66Updated 5 years ago
- REPresentAtion bIas Removal (REPAIR) of datasets☆56Updated 2 years ago
- Supervised NN for pre-training. with group normalization and weight standardization☆30Updated 5 years ago
- ☆73Updated 4 years ago
- Pytorch Implementation of the paper MixMatch: A Holistic Approach to Semi-Supervised Learning (https://arxiv.org/pdf/1905.02249.pdf)☆123Updated 5 years ago
- [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…☆125Updated 3 years ago