lightlightdyy / Deep-Learning-and-Causal-InferenceLinks
☆30Updated 7 years ago
Alternatives and similar repositories for Deep-Learning-and-Causal-Inference
Users that are interested in Deep-Learning-and-Causal-Inference are comparing it to the libraries listed below
Sorting:
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- Feature Interaction Interpretability via Interaction Detection☆35Updated 2 years ago
- ☆40Updated 7 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 3 years ago
- ☆32Updated 7 years ago
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 4 years ago
- ☆65Updated last year
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆54Updated 4 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 5 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆24Updated 3 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆64Updated 5 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆66Updated last year
- Causal Inference & Deep Learning, MIT IAP 2018☆89Updated 7 years ago
- Software relating to relational empirical risk minimization☆17Updated 4 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆131Updated 2 years ago
- CEVAE with VampPrior☆11Updated 7 years ago
- ☆11Updated 7 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆38Updated last year
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆28Updated 4 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆86Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- A short course on temporal point process and modeling irregular time series☆21Updated 5 years ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆49Updated 5 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆112Updated 4 years ago
- Implementation of paper Long-Term Effect Estimation with Surrogate Representation☆14Updated 5 years ago