jhartford / DeepIV

Related projects ⓘ

Alternatives and complementary repositories for DeepIV

• AMLab-Amsterdam / CEVAE
  Causal Effect Inference with Deep Latent-Variable Models
  ☆327Updated 4 years ago
• ijmbarr / notes-on-causal-inference
  Some notes on Causal Inference, with examples in python
  ☆149Updated 4 years ago
• IBM-HRL-MLHLS / IBM-Causal-Inference-Benchmarking-Framework
  Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code
  ☆80Updated 6 years ago
• timmens / causal-forest
  Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
  ☆65Updated 4 years ago
• clinicalml / cfrnet
  Counterfactual Regression
  ☆297Updated last year
• xnie / rlearner
  Quasi-Oracle Estimation of Heterogeneous Treatment Effects
  ☆103Updated 3 years ago
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆43Updated 2 years ago
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆441Updated last year
• blei-lab / deconfounder_tutorial
  ☆87Updated 4 years ago
• napsternxg / awesome-causality
  Resources related to causality
  ☆257Updated 9 months ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆128Updated 4 months ago
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆62Updated 8 months ago
• bd2kccd / py-causal
  ☆204Updated last year
• claudiashi57 / dragonnet
  ☆248Updated 2 years ago
• susanathey / causalTree
  Working repository for Causal Tree and extensions
  ☆435Updated 4 years ago
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆54Updated 4 years ago
• d909b / perfect_match
  ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
  ☆123Updated last year
• vveitch / causality-tutorials
  Short tutorials on the use of machine learning methods for causal inference
  ☆48Updated last year
• vveitch / causal-network-embeddings
  Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"
  ☆55Updated last year
• d909b / drnet
  💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…
  ☆84Updated last year
• swager / causalForest
  DEPRECATED. See new generalized random forest package for up-to-date implementation.
  ☆52Updated 7 years ago
• matthewvowels1 / Awesome-Causal-Inference
  A curated list of awesome work on causal inference, particularly in machine learning.
  ☆96Updated 3 years ago
• kjung / scikit-learn
  A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.
  ☆22Updated 8 years ago
• kochbj / Deep-Learning-for-Causal-Inference
  Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…
  ☆304Updated last month
• grf-labs / policytree
  Policy learning via doubly robust empirical welfare maximization over trees
  ☆77Updated 5 months ago
• ehkennedy / npcausal
  ☆92Updated 10 months ago
• ijmbarr / causalgraphicalmodels
  Causal Graphical Models in Python
  ☆240Updated last year
• franrruiz / shopper-src
  Code for Shopper, a probabilistic model of shopping baskets
  ☆52Updated 4 years ago
• crflynn / skgrf
  scikit-learn compatible Python bindings for grf (generalized random forests) C++ random forest library
  ☆31Updated 2 years ago
• usaito / counterfactual-cv
  (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’
  ☆31Updated last year