Alternatives and similar repositories for causality4ml:

Users that are interested in causality4ml are comparing it to the libraries listed below

• matthewvowels1 / Awesome-Causal-Inference
  A curated list of awesome work on causal inference, particularly in machine learning.
  ☆98Updated 3 years ago
• Osier-Yi / SITE
  ☆58Updated 2 years ago
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆75Updated 3 years ago
• DMIRLAB-Group / SELF
  Provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equ…
  ☆16Updated 7 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…
  ☆71Updated 2 years ago
• d909b / perfect_match
  ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
  ☆125Updated last year
• hlzhang109 / TransTEE
  ☆31Updated 2 years ago
• JeanKaddour / SIN
  Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
  ☆42Updated 2 years ago
• d909b / drnet
  💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…
  ☆86Updated last year
• L-F-Z / CEE
  Causal Effect Engine is a Golang package for causal inference
  ☆18Updated 2 years ago
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆58Updated 4 years ago
• nuster1128 / Awesome-Causal-Papers
  We organize papers related to causal that published on top conferences recently. (因果领域论文分类汇总)
  ☆76Updated last year
• aaronwtr / cfrnet-reproduction
  Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causa…
  ☆16Updated 2 years ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆133Updated 7 months ago
• causal-machine-learning / kdd2021-tutorial
  EconML/CausalML KDD 2021 Tutorial
  ☆161Updated last year
• WeijiaZhang24 / TEDVAE
  Code for TEDVAE, a VAE-based treatment effect estimation algorithm.
  ☆22Updated 2 years ago
• imirzadeh / awesome-causal-inference
  A (concise) curated list of awesome Causal Inference resources.
  ☆225Updated 2 years ago
• causal-machine-learning-lab / mliv
  ☆26Updated 2 years ago
• JackHCC / Awesome-Uplift-Model
  🛠 How to Apply Causal ML to Real Scene Modeling？How to learn Causal ML？【✔从Causal ML到实际场景的Uplift建模】
  ☆122Updated last year
• claudiashi57 / dragonnet
  ☆253Updated 2 years ago
• DMIRLAB-Group / CANM
  This code provide the CANM algorithim for causal discovery. Please cite "Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao. Cau…
  ☆16Updated 5 years ago
• fulifeng / Causal_Reading_Group
  We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NU…
  ☆510Updated last year
• oddrose / cfrnet
  Counterfactual Regression
  ☆23Updated 8 years ago
• anpwu / DeR-CFR
  ☆18Updated 2 years ago
• DAMO-DI-ML / AAAI2022-HCM
  Source code of AAAI'22 paper: A Hybrid Causal Structure Learning Algorithm for Mixed-type Data
  ☆37Updated 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
  ☆81Updated 6 years ago
• DSXiangLi / Paper_CausalInference_abtest
  因果推理&AB实验相关论文小书库
  ☆218Updated last year
• huiyang-yi / Awesome-Causality-and-ML-Papers
  关于causal discovery, invariant learning, machine learning等方向的论文阅读笔记和slides总结
  ☆28Updated last month
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆450Updated last year
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆51Updated 4 years ago