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Dynamask
This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its prediction when the data is represented in terms of time series. For more details on the theoretical side, please read our ICML 2021 paper: 'Explaining Time Series Predictions with Dynamic Masks'.Simplex
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.Label-Free-XAI
This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.FourierDiffusion
This repository implements time series diffusion in the frequency domain.Symbolic-Pursuit
Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"RobustXAI
This repository contains the implementation of the explanation invariance and equivariance metrics, a framework to evaluate the robustness of interpretability methods.ITErpretability
This repository contains the implementation of ITErpretability, a new framework to benchmark treatment effect deep neural network estimators with interpretability. For more details, please read our NeurIPS 2022 paper: 'Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability'.Projet-Ray-Tracing
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