mrojascarulla / causal_transfer_learning
☆30Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for causal_transfer_learning
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 3 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆29Updated 5 years ago
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆19Updated last year
- ☆37Updated 5 years ago
- ☆27Updated 4 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆21Updated last year
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 3 years ago
- Self-Explaining Neural Networks☆13Updated last year
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 3 years ago
- ☆33Updated 5 years ago
- ☆43Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆35Updated last year
- Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant predictio…☆20Updated 9 months ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆34Updated 2 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Updated 2 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- ☆65Updated 4 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆26Updated 4 years ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆25Updated 2 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 2 years ago
- An Empirical Study of Invariant Risk Minimization☆28Updated 4 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆80Updated 7 months ago
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 3 years ago
- Training quantile models☆40Updated 3 years ago
- Code for the ICML 2019 paper: Distribution Calibration for Regression☆21Updated last year
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆31Updated 3 years ago
- ☆10Updated 5 years ago