Alternatives and similar repositories for CEVAE

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

• clinicalml / cfrnet
  Counterfactual Regression
  ☆308Updated 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
• xunzheng / notears
  DAGs with NO TEARS: Continuous Optimization for Structure Learning
  ☆630Updated last year
• claudiashi57 / dragonnet
  ☆271Updated 3 years ago
• bd2kccd / py-causal
  ☆206Updated 2 years ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆142Updated last year
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆468Updated 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
• 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
• 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
  ☆83Updated 7 years ago
• Osier-Yi / SITE
  ☆58Updated 3 years ago
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆61Updated 5 years ago
• amit-sharma / causal-inference-tutorial
  Repository with code and slides for a tutorial on causal inference.
  ☆577Updated 5 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆99Updated 5 years ago
• keiichishima / pcalg
  CPDAG Estimation using PC-Algorithm
  ☆96Updated 3 years ago
• blei-lab / deconfounder_tutorial
  ☆87Updated 5 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…
  ☆329Updated 8 months ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆216Updated 3 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• fishmoon1234 / DAG-GNN
  ☆311Updated 3 years ago
• ijmbarr / notes-on-causal-inference
  Some notes on Causal Inference, with examples in python
  ☆153Updated 5 years ago
• cdt15 / lingam
  Python package for causal discovery based on LiNGAM.
  ☆426Updated last week
• FenTechSolutions / CausalDiscoveryToolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆1,181Updated last year
• 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
• biomedia-mira / deepscm
  Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
  ☆281Updated last year
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• kurowasan / GraN-DAG
  ☆93Updated 2 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 4 years ago
• laurencium / Causalinference
  Causal Inference in Python
  ☆568Updated 4 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago