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Search results for machine learning causality
causality
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machine-learning
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32 search results found
Dowhy
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6,730
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.
Rath
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3,717
Next generation of automated data exploratory analysis and visualization platform.
Econml
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3,522
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of
Generalization Causality
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993
关于domain generalization,domain adaptation,causality,robutness,prompt,optimization model各式各样研究的阅读笔记
Causaldiscoverytoolbox
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804
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Causalml
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665
The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML
Causallib
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653
A Python package for modular causal inference analysis and model evaluations
Scikit Uplift
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572
❗ uplift modeling in scikit-learn style in python 🐍
Causal_reading_group
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361
We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.
Lingam
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312
Python package for causal discovery based on LiNGAM.
Looper
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201
A resource list for causality in statistics, data science and physics
Awesome Causal Inference
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169
A (concise) curated list of awesome Causal Inference resources.
Robustdg
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160
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Tcdf
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121
Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
Pycopent
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101
Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Independence), and the statistics for multivariate normality test and two-sample test in Python
Causeinfer
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54
Machine learning based causal inference/uplift in Python
Benchpress
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52
A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.
Causal Gen
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41
(ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models
Copent
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35
R package for estimating copula entropy (mutual information), transfer entropy (conditional independence), and the statistic for multivariate normality test and two-sample test
Openasce
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35
OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, causal effect estimation and attribution algorithms all in one package.
Causalgraph
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34
A python package for modeling, persisting and visualizing causal graphs embedded in knowledge graphs.
Invariant Risk Minimization
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32
Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
Gvar
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26
An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
Time Robust Forest
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14
Leverage timestamp information to improve Random Forest out of distribution generalization.
Cfml_tools
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12
My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context
Recourse
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12
Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
Unicorn
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10
A Framework for Reasoning about System Performance using Causal AI
Ctl
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7
A causal tree method for heterogeneous treatment effects in Python
Causality4rec_paperlist
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7
This repository collects recent top papers about causal inference for recommendation. We will keep updating the paper list weekly.
Causai
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7
Causai is a Python package for Causality in Machine Learning. We provide state-of-the-art causal algorithms and ML into decision-making systems
Shapflex
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5
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
Graphical_model_learning
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5
Learning graphical models, with a focus on causal models and learning from interventional data.
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