marcoancona / DeepExplainLinks
A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)
☆761Updated 5 years ago
Alternatives and similar repositories for DeepExplain
Users that are interested in DeepExplain are comparing it to the libraries listed below
Sorting:
- Public facing deeplift repo☆872Updated 3 years ago
- A toolbox to iNNvestigate neural networks' predictions!☆1,306Updated 7 months ago
- Attributing predictions made by the Inception network using the Integrated Gradients method☆640Updated 3 years ago
- The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…☆335Updated 3 years ago
- Code for the TCAV ML interpretability project☆648Updated 5 months ago
- ☆918Updated 2 years ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆840Updated 3 years ago
- Interpretability Methods for tf.keras models with Tensorflow 2.x☆1,036Updated last year
- Code for "High-Precision Model-Agnostic Explanations" paper☆812Updated 3 years ago
- Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).☆989Updated last year
- Layer-wise Relevance Propagation (LRP) for LSTMs.☆225Updated 5 years ago
- Bayesian Deep Learning Benchmarks☆672Updated 2 years ago
- Code for all experiments.☆318Updated 4 years ago
- Implementation of Layerwise Relevance Propagation for heatmapping "deep" layers☆98Updated 7 years ago
- Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human…☆74Updated 3 years ago
- ☆100Updated 7 years ago
- Building a Bayesian deep learning classifier☆491Updated 8 years ago
- Tuning hyperparams fast with Hyperband☆596Updated 7 years ago
- Tensorflow tutorial for various Deep Neural Network visualization techniques☆346Updated 5 years ago
- Data Shapley: Equitable Valuation of Data for Machine Learning☆281Updated last year
- All about explainable AI, algorithmic fairness and more☆110Updated 2 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆631Updated 4 months ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆85Updated 2 years ago
- apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models qui…☆524Updated 2 weeks ago
- Interpretability and explainability of data and machine learning models☆1,746Updated 9 months ago
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆237Updated 4 months ago
- Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet☆624Updated 2 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- Library of transfer learners and domain-adaptive classifiers.☆93Updated 6 years ago