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100 public repositories
matching this topic...
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Updated
May 29, 2024
Python
A Python library that helps data scientists to infer causation rather than observing correlation.
Updated
May 21, 2024
Python
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Updated
Apr 2, 2024
Python
Must-read papers and resources related to causal inference and machine (deep) learning
A Python package for modular causal inference analysis and model evaluations
Updated
Oct 25, 2023
Python
YLearn, a pun of "learn why", is a python package for causal inference
Updated
Mar 15, 2024
Python
Python package for causal discovery based on LiNGAM.
Updated
May 17, 2024
Python
A Python package for causal inference using Synthetic Controls
Updated
Jan 25, 2024
Python
Python library for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Updated
May 23, 2024
Jupyter Notebook
Streamline a data analysis process
Updated
Apr 11, 2024
HTML
A resource list for causality in statistics, data science and physics
CAusal Reasoning for Network Identification with integer VALue programming in R
This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.
Updated
Nov 26, 2022
Python
Causal Inference & Deep Learning, MIT IAP 2018
Create soft prompts for fairseq 13B dense, GPT-J-6B and GPT-Neo-2.7B for free in a Google Colab TPU instance
Updated
Mar 1, 2023
Python
Uplift modeling and evaluation library. Actively maintained pypi version.
Updated
Dec 28, 2023
Python
Python package for the creation, manipulation, and learning of Causal DAGs
Updated
Apr 12, 2023
JavaScript
A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.
Updated
May 30, 2024
Python
A list of Graph Causal Learning materials.
🛠 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】
Updated
Mar 25, 2023
Jupyter Notebook
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