Alternatives and similar repositories for CEVAE

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

• clinicalml / cfrnet
  Counterfactual Regression
  ☆307Updated 2 years ago
• d909b / perfect_match
  ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
  ☆128Updated 2 years ago
• bd2kccd / py-causal
  ☆205Updated 2 years ago
• xunzheng / notears
  DAGs with NO TEARS: Continuous Optimization for Structure Learning
  ☆628Updated last year
• claudiashi57 / dragonnet
  ☆268Updated 3 years ago
• jhartford / DeepIV
  Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction
  ☆156Updated 3 years ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆140Updated 11 months ago
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆61Updated 5 years ago
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆467Updated last year
• 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
• 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
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆213Updated 3 years ago
• fishmoon1234 / DAG-GNN
  ☆309Updated 3 years ago
• Osier-Yi / SITE
  ☆58Updated 3 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
• FenTechSolutions / CausalDiscoveryToolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆1,177Updated last year
• blei-lab / deconfounder_tutorial
  ☆87Updated 5 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 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
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆47Updated 3 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• maxwshen / iap-cidl
  Causal Inference & Deep Learning, MIT IAP 2018
  ☆88Updated 7 years ago
• kurowasan / GraN-DAG
  ☆92Updated 2 years ago
• biomedia-mira / deepscm
  Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
  ☆281Updated last year
• jvpoulos / causal-ml
  Must-read papers and resources related to causal inference and machine (deep) learning
  ☆717Updated 2 years ago
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆131Updated 4 years ago
• kevinsbello / dagma
  A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…
  ☆119Updated last year
• ijmbarr / notes-on-causal-inference
  Some notes on Causal Inference, with examples in python
  ☆153Updated 5 years ago