alshedivat / cen
Contextual Explanation Networks (CEN).
☆11Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for cen
- Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"☆15Updated 2 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆28Updated 3 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated 6 months ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆35Updated last year
- Code for the paper "Model Agnostic Interpretability for Multiple Instance Learning".☆13Updated 2 years ago
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆30Updated 3 years ago
- Causal data augmentation for pretraining debiasing☆11Updated 3 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …☆24Updated last year
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 3 years ago
- ☆16Updated 2 years ago
- Self-Explaining Neural Networks☆39Updated 4 years ago
- Official Implementation of "Doubly Mixed-Effects Gaussian Process Regression" (Jun Ho Yoon, Daniel P. Jeong, Seyoung Kim) (AISTATS 2022, …☆11Updated 2 years ago
- This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For m…☆23Updated 2 years ago
- Code for "Neural causal learning from unknown interventions"☆99Updated 4 years ago
- Code to study the generalisability of benchmark models on non-stationary EHRs.☆14Updated 5 years ago
- Explanation Optimization☆13Updated 4 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆28Updated 2 years ago
- ☆30Updated 6 years ago
- Tools for robustness evaluation in interpretability methods☆11Updated 3 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆56Updated 8 months ago
- Code for the ICLR 2021 Paper "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"☆12Updated 3 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆30Updated last year
- SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks☆13Updated last year
- Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019☆13Updated 5 years ago
- Experiments with experimental rule-based models to go along with imodels.☆15Updated 2 weeks ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.☆8Updated 4 years ago
- Self-Explaining Neural Networks☆13Updated last year