genome_integration
awesome-causality-algorithms
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11 | 2,796 | |
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0.0 | 3.5 | |
almost 2 years ago | 9 months ago | |
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MIT License | MIT License |
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genome_integration
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[D] Clustering high dimensional
Causal Genomic Analysis
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)
What are some alternatives?
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
looper - A resource list for causality in statistics, data science and physics
CausalPy - A Python package for causal inference in quasi-experimental settings
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
enformer-pytorch - Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
spotlight - Deep recommender models using PyTorch.
causalml - Uplift modeling and causal inference with machine learning algorithms
HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.
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.