Alternatives and similar repositories for causality-course-ethz

Users that are interested in causality-course-ethz are comparing it to the libraries listed below

• Chrisejorge / Causal-Inference
  Materials Collection for Causal Inference
  ☆47Updated 2 years ago
• CausalAIBook / MetricsMLNotebooks
  Notebooks for Applied Causal Inference Powered by ML and AI
  ☆141Updated 9 months ago
• vdorie / aciccomp
  Code to run submissions for the Atlantic Causal Inference Competition
  ☆43Updated last year
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• bradyneal / causal-book-code
  ☆81Updated 5 years ago
• jaredsmurray / bcf
  Bayesian Causal Forests
  ☆50Updated last year
• annennenne / causalDisco
  Tools for causal discovery in R
  ☆20Updated 9 months ago
• anishazaveri / austen_plots
  Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".
  ☆27Updated 4 years ago
• dobriban / Topics-in-deep-learning
  Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
  ☆94Updated 2 years ago
• vveitch / causality-tutorials
  Short tutorials on the use of machine learning methods for causal inference
  ☆50Updated 3 years ago
• d2cml-ai / 14.388_py
  This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI …
  ☆17Updated 2 years ago
• max-little / GRAPL
  GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference
  ☆83Updated last year
• napsternxg / awesome-causality
  Resources related to causality
  ☆266Updated last year
• bradyneal / causal-inference-books
  Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…
  ☆60Updated 6 years ago
• caus-am / jci
  Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)
  ☆16Updated 5 years ago
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆50Updated 3 years ago
• csquires / 6.S091-causality
  ☆194Updated 2 years ago
• CausalInference / pygformula
  The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…
  ☆30Updated last month
• ryantibs / statlearn-s23
  Course materials for Advanced Topics in Statistical Learning, Spring 2023
  ☆49Updated 5 months ago
• stanford-msande228 / winter23
  ☆23Updated last year
• d2cml-ai / mgtecon634_py
  This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…
  ☆14Updated 2 years ago
• ryantibs / statlearn-s24
  Course materials for Advanced Topics in Statistical Learning, Spring 2024
  ☆26Updated 5 months 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…
  ☆340Updated last year
• TianyiPeng / causaltensor
  A python package for causal inference in panels
  ☆13Updated last month
• hammadshaikhha / Causal-Inference-Mastery
  Notes and simulations on graduate level causal inference in statistics with applications to social sciences.
  ☆23Updated 6 years ago
• christinaheinze / CompareCausalNetworks
  A unified interface for the estimation of causal networks
  ☆22Updated 5 years ago
• cliburn / sta-663-2021
  Computational Statistics and Statistical Computing
  ☆37Updated 4 years ago
• soerenkuenzel / causalToolbox
  ☆44Updated 4 years ago
• Ci2Lab / Applied_Causal_Inference_Course
  This course is an overview of applied causal inference.
  ☆55Updated 7 months ago
• kyunghyuncho / 2024-causal-inference-machine-learning
  ☆29Updated last year