lightlightdyy / Deep-Learning-and-Causal-InferenceLinks
☆30Updated 6 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 our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- ☆32Updated 7 years ago
- CEVAE with VampPrior☆11Updated 7 years ago
- ☆65Updated last year
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 4 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆43Updated 3 years ago
- Feature Interaction Interpretability via Interaction Detection☆35Updated 2 years ago
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 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☆23Updated 2 years ago
- 🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…☆42Updated 2 years ago
- ☆40Updated 6 years ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Updated 3 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆63Updated 5 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- Causal Inference & Deep Learning, MIT IAP 2018☆89Updated 7 years ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 5 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- ☆32Updated 4 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆28Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- ☆43Updated 7 years ago
- ☆11Updated 7 years ago
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10Updated 7 years ago