Alternatives and similar repositories for dragonnet

Users that are interested in dragonnet are comparing it to the libraries listed below

• clinicalml / cfrnet
  Counterfactual Regression
  ☆310Updated 2 years ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆142Updated last year
• d909b / drnet
  💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…
  ☆88Updated 2 years ago
• d909b / perfect_match
  ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
  ☆129Updated 2 years ago
• lushleaf / varying-coefficient-net-with-functional-tr
  [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…
  ☆78Updated 2 years ago
• oddrose / cfrnet
  Counterfactual Regression
  ☆25Updated 9 years ago
• Osier-Yi / SITE
  ☆58Updated 3 years ago
• AMLab-Amsterdam / CEVAE
  Causal Effect Inference with Deep Latent-Variable Models
  ☆343Updated 4 years ago
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆471Updated last year
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆61Updated 5 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
  ☆84Updated 7 years ago
• farazmah / dragonnet-pytorch
  pytorch implementation of dragonnet
  ☆43Updated 2 years ago
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆64Updated last year
• 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…
  ☆330Updated 8 months ago
• causal-machine-learning / kdd2021-tutorial
  EconML/CausalML KDD 2021 Tutorial
  ☆160Updated last year
• xunzheng / notears
  DAGs with NO TEARS: Continuous Optimization for Structure Learning
  ☆634Updated last year
• jhartford / DeepIV
  Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction
  ☆156Updated 4 years ago
• anpwu / DeR-CFR
  ☆20Updated 3 years ago
• jvpoulos / causal-ml
  Must-read papers and resources related to causal inference and machine (deep) learning
  ☆729Updated 2 years ago
• sschrod / BITES
  BITES: Balanced Individual Treatment Effect for Survival data
  ☆18Updated last year
• Ibotta / mr_uplift
  Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…
  ☆69Updated 2 months ago
• anthem-ai / bcauss
  Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"
  ☆24Updated 2 years ago
• kailiang-zhong / DESCN
  Implementation of paper DESCN, which is accepted in SIGKDD 2022.
  ☆91Updated last year
• bd2kccd / py-causal
  ☆205Updated 2 years ago
• hlzhang109 / TransTEE
  ☆34Updated 3 years ago
• criteo-research / large-scale-ITE-UM-benchmark
  ☆22Updated 3 years ago
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆75Updated 4 years ago
• amit-sharma / causal-inference-tutorial
  Repository with code and slides for a tutorial on causal inference.
  ☆576Updated 5 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• google / lifetime_value
  ☆354Updated 11 months ago