Alternatives and similar repositories for cfrnet

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

• AMLab-Amsterdam / CEVAE
  Causal Effect Inference with Deep Latent-Variable Models
  ☆345Updated 5 years ago
• claudiashi57 / dragonnet
  ☆276Updated 3 years ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆143Updated last year
• d909b / drnet
  💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…
  ☆90Updated 2 years ago
• Osier-Yi / SITE
  ☆58Updated 3 years ago
• xunzheng / notears
  DAGs with NO TEARS: Continuous Optimization for Structure Learning
  ☆641Updated last year
• lushleaf / varying-coefficient-net-with-functional-tr
  [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…
  ☆81Updated 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
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆61Updated 5 years ago
• bd2kccd / py-causal
  ☆204Updated 2 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
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆472Updated last year
• oddrose / cfrnet
  Counterfactual Regression
  ☆25Updated 9 years ago
• jhartford / DeepIV
  Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction
  ☆156Updated 4 years ago
• logangraham / arXausality
  A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.
  ☆416Updated 4 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…
  ☆331Updated 9 months ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• sschrod / BITES
  BITES: Balanced Individual Treatment Effect for Survival data
  ☆18Updated 2 years ago
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆49Updated 3 years ago
• blei-lab / deconfounder_tutorial
  ☆87Updated 5 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• jvpoulos / causal-ml
  Must-read papers and resources related to causal inference and machine (deep) learning
  ☆730Updated 2 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆77Updated 4 years ago
• keiichishima / pcalg
  CPDAG Estimation using PC-Algorithm
  ☆95Updated 3 years ago
• FenTechSolutions / CausalDiscoveryToolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆1,186Updated last year
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆64Updated last year
• hlzhang109 / TransTEE
  ☆35Updated 3 years ago
• amit-sharma / causal-inference-tutorial
  Repository with code and slides for a tutorial on causal inference.
  ☆577Updated 5 years ago
• ioanabica / SCIGAN
  Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bica…
  ☆30Updated 4 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