Alternatives and similar repositories for Integrated-Gradients

Users that are interested in Integrated-Gradients are comparing it to the libraries listed below

• marcoancona / DeepExplain
  A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also in…
  ☆757Updated 5 years ago
• tensorflow / tcav
  Code for the TCAV ML interpretability project
  ☆645Updated 4 months ago
• kundajelab / deeplift
  Public facing deeplift repo
  ☆865Updated 3 years ago
• TianhongDai / integrated-gradient-pytorch
  This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.
  ☆187Updated 3 years ago
• kohpangwei / influence-release
  ☆797Updated 4 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• lopusz / awesome-interpretable-machine-learning
  ☆916Updated 2 years ago
• sebastian-lapuschkin / lrp_toolbox
  The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Py…
  ☆333Updated 3 years ago
• marcotcr / lime-experiments
  Code for all experiments.
  ☆318Updated 4 years ago
• amiratag / DataShapley
  Data Shapley: Equitable Valuation of Data for Machine Learning
  ☆280Updated last year
• gpleiss / temperature_scaling
  A simple way to calibrate your neural network.
  ☆1,162Updated 2 months ago
• anguyen8 / XAI-papers
  ☆607Updated 2 years ago
• marcotcr / anchor
  Code for "High-Precision Model-Agnostic Explanations" paper
  ☆807Updated 3 years ago
• albermax / innvestigate
  A toolbox to iNNvestigate neural networks' predictions!
  ☆1,302Updated 6 months ago
• alvinwan / neural-backed-decision-trees
  Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
  ☆623Updated 2 years ago
• Jianbo-Lab / L2X
  ☆124Updated 4 years ago
• amiratag / ACE
  Towards Automatic Concept-based Explanations
  ☆161Updated last year
• adebayoj / sanity_checks_saliency
  ☆112Updated 2 years ago
• p-lambda / wilds
  A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
  ☆579Updated last year
• laura-rieger / deep-explanation-penalization
  Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…
  ☆128Updated 4 years ago
• BeenKim / MMD-critic
  ☆134Updated 6 years ago
• suinleelab / path_explain
  A repository for explaining feature attributions and feature interactions in deep neural networks.
  ☆189Updated 3 years ago
• ArrasL / LRP_for_LSTM
  Layer-wise Relevance Propagation (LRP) for LSTMs.
  ☆225Updated 5 years ago
• nimarb / pytorch_influence_functions
  This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…
  ☆341Updated last year
• 1202kbs / Understanding-NN
  Tensorflow tutorial for various Deep Neural Network visualization techniques
  ☆346Updated 5 years ago
• PAIR-code / saliency
  Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
  ☆985Updated last year
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆132Updated 5 years ago
• amarasovic / interpretability-literature
  ☆264Updated 5 years ago
• pbiecek / xai_resources
  Interesting resources related to XAI (Explainable Artificial Intelligence)
  ☆839Updated 3 years ago
• idiap / fullgrad-saliency
  Full-gradient saliency maps
  ☆212Updated 2 years ago