seedatnabeel / TE-CDE
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
☆27Updated 2 years ago
Alternatives and similar repositories for TE-CDE:
Users that are interested in TE-CDE are comparing it to the libraries listed below
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆26Updated 3 years ago
- ☆38Updated 6 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- 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
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 4 years ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆35Updated 2 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆82Updated last year
- ☆24Updated 2 weeks ago
- ☆30Updated last year
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 3 years ago
- ☆60Updated 4 years ago
- Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.☆24Updated 2 years ago
- ☆23Updated 2 years ago
- ☆44Updated 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 2 years ago
- ☆30Updated 3 years ago
- Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)☆84Updated 4 years ago
- VAEs and nonlinear ICA: a unifying framework☆34Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆62Updated 2 months ago
- Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.☆8Updated 4 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- Training quantile models☆43Updated 5 months ago
- Deep Counterfactual Prediction with Categorical Backward Variables☆12Updated 2 years ago
- Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…☆21Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆74Updated 4 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆45Updated 2 years ago
- Diffusion Models for Causal Discovery☆85Updated 2 years ago
- Implementation of the ICML 2024 paper "Discovering Mixtures of Structural Causal Models from Time Series Data"☆21Updated 6 months ago