MLforHealth / CausalDALinks
Causal data augmentation for pretraining debiasing
☆11Updated 4 years ago
Alternatives and similar repositories for CausalDA
Users that are interested in CausalDA are comparing it to the libraries listed below
Sorting:
- Code for "Generative causal explanations of black-box classifiers"☆35Updated 4 years ago
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆45Updated 5 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Updated 2 years ago
- SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks☆13Updated 2 years ago
- ☆14Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆62Updated last year
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆26Updated 4 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …☆24Updated 2 years ago
- Tensorflow implementation for the Class-wise Selective Rationalization☆14Updated 2 years ago
- Code for "Neural causal learning from unknown interventions"☆105Updated 5 years ago
- ☆17Updated 6 years ago
- ☆32Updated 7 years ago
- Tools for robustness evaluation in interpretability methods☆10Updated 4 years ago
- Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"☆15Updated 3 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- Local explanations with uncertainty 💐!☆40Updated 2 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- ☆44Updated 3 years ago
- ☆31Updated 3 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- Implementation of paper "Probabilistic Active Meta-Learning" (NeurIPS 2020).☆20Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆64Updated 5 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Self-Explaining Neural Networks☆13Updated 2 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)☆22Updated 2 years ago
- Code and webpages for our study on teaching humans to defer to an AI☆11Updated last year
- 🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…☆42Updated 2 years ago