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)
☆760Aug 25, 2020Updated 5 years ago
Alternatives and similar repositories for DeepExplain
Users that are interested in DeepExplain are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Public facing deeplift repo☆875Apr 28, 2022Updated 4 years ago
- A toolbox to iNNvestigate neural networks' predictions!☆1,306Apr 11, 2025Updated last year
- The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…☆335Jun 13, 2022Updated 4 years ago
- Attributing predictions made by the Inception network using the Integrated Gradients method☆651Feb 23, 2022Updated 4 years ago
- Interpretability Methods for tf.keras models with Tensorflow 2.x☆1,038Jun 3, 2024Updated 2 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)☆62Jul 1, 2019Updated 6 years ago
- A game theoretic approach to explain the output of any machine learning model.☆25,563Jun 22, 2026Updated last week
- Layer-wise Relevance Propagation (LRP) for LSTMs.☆225Apr 24, 2020Updated 6 years ago
- A collection of infrastructure and tools for research in neural network interpretability.☆4,707Feb 6, 2023Updated 3 years ago
- ☆917Mar 19, 2023Updated 3 years ago
- Algorithms for explaining machine learning models☆2,635Oct 17, 2025Updated 8 months ago
- Fit interpretable models. Explain blackbox machine learning.☆6,881Jun 22, 2026Updated last week
- Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).☆997Mar 20, 2024Updated 2 years ago
- TF MOtif Discovery from Importance SCOres☆185May 13, 2026Updated last month
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- A curated list of awesome responsible machine learning resources.☆4,046Jun 3, 2026Updated 3 weeks ago
- Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!☆29Jul 13, 2019Updated 6 years ago
- Code for "High-Precision Model-Agnostic Explanations" paper☆813Jul 19, 2022Updated 3 years ago
- Lime: Explaining the predictions of any machine learning classifier☆12,143Jul 25, 2024Updated last year
- ☆117Nov 21, 2022Updated 3 years ago
- Code for the paper: Towards Better Understanding Attribution Methods. CVPR 2022.☆17Jun 13, 2022Updated 4 years ago
- Supervised Local Modeling for Interpretability☆29Oct 27, 2018Updated 7 years ago
- Official repository for "Bridging Adversarial Robustness and Gradient Interpretability".☆29May 2, 2019Updated 7 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Mar 22, 2021Updated 5 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Code for the TCAV ML interpretability project☆653May 5, 2026Updated last month
- Python/Keras implementation of integrated gradients presented in "Axiomatic Attribution for Deep Networks" for explaining any model defin…☆217Apr 28, 2018Updated 8 years ago
- A repository for explaining feature attributions and feature interactions in deep neural networks.☆193Jan 16, 2022Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Jul 19, 2021Updated 4 years ago
- ☆124May 10, 2021Updated 5 years ago
- Understanding Deep Networks via Extremal Perturbations and Smooth Masks☆350Jul 22, 2020Updated 5 years ago
- ☆261Dec 10, 2019Updated 6 years ago
- Pytorch Implementation of recent visual attribution methods for model interpretability☆146Feb 27, 2020Updated 6 years ago
- Model zoo for genomics☆174Dec 17, 2025Updated 6 months ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- HIVE: Evaluating the Human Interpretability of Visual Explanations (ECCV 2022)☆22Jan 19, 2023Updated 3 years ago
- Code/figures in Right for the Right Reasons☆57Dec 29, 2020Updated 5 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,518Jul 13, 2025Updated 11 months ago
- ☆100Mar 29, 2018Updated 8 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆126Aug 25, 2021Updated 4 years ago
- Tools for training explainable models using attribution priors.☆128Mar 19, 2021Updated 5 years ago
- H2O.ai Machine Learning Interpretability Resources☆492Dec 12, 2020Updated 5 years ago