rguo12 / network-deconfounder-wsdm20Links
Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
β75Updated 4 years ago
Alternatives and similar repositories for network-deconfounder-wsdm20
Users that are interested in network-deconfounder-wsdm20 are comparing it to the libraries listed below
Sorting:
- ππ Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatmβ¦β90Updated 2 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.β25Updated 2 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. β¦β52Updated 4 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"β57Updated 2 years ago
- Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensigβ¦β21Updated 3 years ago
- ββ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.β129Updated 2 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring codeβ84Updated 7 years ago
- β59Updated 3 years ago
- β46Updated last year
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bicaβ¦β30Updated 4 years ago
- β45Updated 6 years ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018β62Updated 5 years ago
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"β18Updated 2 years ago
- β314Updated 3 years ago
- Implementation of the CTDNE algorithm.β20Updated 6 years ago
- Counterfactual Regressionβ25Updated 9 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)β43Updated 3 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.β143Updated last year
- Causal Inferenceβ10Updated 5 years ago
- β40Updated 6 years ago
- Variational Autoencoders for Marked Point Processesβ15Updated 5 years ago
- β95Updated 2 years ago
- Datasets for Causal-Structure-Learning Repoβ15Updated 5 years ago
- A pytorch implementation of ERPP and RMTPP on ATM maintenance dataset.β54Updated 6 years ago
- β46Updated 3 years ago
- Attentive Neural Point Processes for Event Forecasting, AAAI 2021β18Updated 4 years ago
- Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causaβ¦β18Updated 3 years ago
- Source code of the neural Hawkes particle smoothing (ICML 2019)β43Updated 6 years ago
- β35Updated 3 years ago
- Explainable recommendation via interpretable feature mappingβ18Updated 5 years ago