OATML / causal-bald
☆15Updated 10 months ago
Related projects ⓘ
Alternatives and complementary repositories for causal-bald
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- ☆30Updated 6 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆27Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆34Updated last year
- Project on Causal Machine learning CS 7290☆16Updated 4 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Updated 5 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆68Updated 3 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 3 years ago
- ☆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
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.☆17Updated 8 months ago
- ☆42Updated 2 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆86Updated 9 months ago
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 3 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆27Updated 3 years ago
- python code for kernel methods☆36Updated 5 years 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
- Code for "Neural causal learning from unknown interventions"☆99Updated 4 years ago
- ☆21Updated 11 months ago
- ☆12Updated 11 months ago
- Python package for evaluating model calibration in classification☆19Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".☆10Updated 6 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 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
- Contains all materials for the paper "A counterfactual simulation model of causal judgment".☆22Updated 3 years ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆18Updated 2 years ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆31Updated last year