deshen24 / syntheticNNLinks
☆25Updated 4 years ago
Alternatives and similar repositories for syntheticNN
Users that are interested in syntheticNN are comparing it to the libraries listed below
Sorting:
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆27Updated 4 years ago
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated last year
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆45Updated 2 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago
- ☆30Updated last year
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 4 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated last year
- ☆16Updated last year
- Conditional calibration of conformal p-values for outlier detection.☆37Updated 3 years ago
- A python package for causal inference in panels☆13Updated last month
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆26Updated 3 years ago
- Causal Inference in Python☆44Updated 2 months ago
- Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)☆32Updated 2 years ago
- The package is developed for treatment recommendation & pairwise treatment individual effect estimation (ITE/CATE/HTE) when multiple trea…☆11Updated 2 years ago
- A package for conformal prediction with conditional guarantees.☆67Updated 2 months ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated last year
- Non-parametrics for Causal Inference☆50Updated 3 years ago
- Notebooks for Applied Causal Inference Powered by ML and AI☆141Updated 9 months ago
- ☆40Updated 7 years ago
- Short tutorials on the use of machine learning methods for causal inference☆50Updated 3 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆66Updated last year
- ☆11Updated 7 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆85Updated 4 years ago
- This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…☆14Updated 2 years ago
- Code associated with paper: Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models, Chernozhuk…☆16Updated 4 years ago
- An R package to estimate the effect of interventions on univariate time series using ARIMA models☆25Updated last year
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated 5 months ago
- Design of Simulations using WGAN☆55Updated 3 years ago
- ☆24Updated 2 years ago
- Code for Colangelo and Lee (2025)☆16Updated 10 months ago