causal-learn VS sections

Compare causal-learn vs sections and see what are their differences.

Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
causal-learn sections
1 6
982 16
5.6% -
7.9 1.8
13 days ago about 2 years ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

causal-learn

Posts with mentions or reviews of causal-learn. We have used some of these posts to build our list of alternatives and similar projects.

sections

Posts with mentions or reviews of sections. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-13.

What are some alternatives?

When comparing causal-learn and sections you can also consider the following projects:

dowhy - 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.

dotwiz - A blazing fast dict subclass that supports dot access notation.

dodiscover - [Experimental] Global causal discovery algorithms

br4nch - br4nch - Data Structure Tree Builder for Python.

tfcausalimpact - Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.

react-intersection-observer - React implementation of the Intersection Observer API to tell you when an element enters or leaves the viewport.

looper - A resource list for causality in statistics, data science and physics

scroll-out - ScrollOut detects changes in scroll for reveal, parallax, and CSS Variable effects!

HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.

Booklet - Making Booklet file from your own PDF

Structure_threader - A wrapper program to parallelize and automate runs of "Structure", "fastStructure" and "MavericK".

The-Definite-Guide-to-Graph-Problems - Code for the Definite Guide to Graph Problems exercises