awesome-causality-algorithms
genome_integration
awesome-causality-algorithms | genome_integration | |
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2,818 | 11 | |
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3.5 | 0.0 | |
10 months ago | almost 2 years ago | |
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MIT License | MIT License |
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awesome-causality-algorithms
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Why the world needs computational social science
https://github.com/rguo12/awesome-causality-algorithms
"The limits of graphical causal discovery" (2021)
genome_integration
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[D] Clustering high dimensional
Causal Genomic Analysis
What are some alternatives?
looper - A resource list for causality in statistics, data science and physics
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
CausalPy - A Python package for causal inference in quasi-experimental settings
spotlight - Deep recommender models using PyTorch.
enformer-pytorch - Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.
causalml - Uplift modeling and causal inference with machine learning algorithms
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.
pgmpy - Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
causal-learn - Causal Discovery in Python. It also includes (conditional) independence tests and score functions.