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causal-inference
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Uplift modeling and causal inference with machine learning algorithms
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Jun 13, 2022 - Python
Coz: Causal Profiling
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Mar 11, 2022 - C
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 Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
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Jun 17, 2022 - Jupyter Notebook
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
python
statistics
simulation
statistical-inference
causality
bayesian-networks
probabilistic-graphical-models
dag
causal-inference
structure-learning
causal-models
sampling-methods
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May 25, 2022 - Python
An index of algorithms for learning causality with data
awesome
learning-to-rank
recommender-system
causality
causality-analysis
causal-inference
multilabel-classification
baselines
causality-algorithms
unconfoundedness-assumption
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Jun 9, 2022
A Python library that helps data scientists to infer causation rather than observing correlation.
data-science
machine-learning
bayesian-inference
bayesian-networks
causal-inference
causal-models
causal-networks
causalnex
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Jun 9, 2022 - Python
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
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Jun 16, 2022 - Jupyter Notebook
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
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Jan 8, 2022 - Jupyter Notebook
Resources to learn more about Machine Learning and Artificial Intelligence
machine-learning
natural-language-processing
information-retrieval
reinforcement-learning
deep-learning
artificial-intelligence
knowledge-graph
question-answering
probabilistic-programming
bayesian-inference
recommender-systems
causal-inference
knowledge-representation
reasoning
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Feb 8, 2022
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
python
machine-learning
algorithm
graph
inference
toolbox
causality
causal-inference
causal-models
graph-structure-recovery
causal-discovery
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Apr 12, 2022 - Python
tibshirani
commented
Sep 5, 2018
I ran a regression_forest for > 10 minutes and had no idea if it would complete in 15 min or an hour.
It would be great to have an argument "verbose" (default FALSE) which causes the function to
print the function's progress, to help the user estimate the remaining time before completion.
feature
good first issue
A good issue to look at when first starting to contribute to the package (expected to be simpler).
maks-sh
commented
Aug 16, 2021
📚 Documentation
It is important that when you click on external links in the documentation, the pages open in a new tab so that the user can quickly return to the documentation site
documentation
Improvements or additions to documentation
good first issue
Good for newcomers
ODS Summer of Code
Causal Discovery for Python. Translation and extension of the Tetrad Java code.
python
time-series
graph
structure
causality
causal-inference
causal
tetrad
continous
confounder
causal-discovery
hidden-causal
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Jun 18, 2022 - Python
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Apr 14, 2022 - R
Statistical Rethinking (2nd ed.) with NumPyro
python
numpy
variational-inference
causal-inference
bayesian-statistics
markov-chain-monte-carlo
laplace-approximation
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Apr 4, 2022 - Jupyter Notebook
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.
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Apr 28, 2022
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
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May 5, 2022 - Python
Open-source Python library for statistical analysis of randomised control trials (A/B tests)
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Mar 31, 2021 - Python
Must-read papers and resources related to causal inference and machine (deep) learning
representation-learning
causal-inference
treatment-effects
causal-models
counterfactual
randomized-controlled-trials
paper-list
heterogeneous-treatment-effects
causal-discovery
counterfactual-learning
estimating-treatment-effects
causal-learning
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May 24, 2022
CausalLift: Python package for causality-based Uplift Modeling in real-world business
econometrics
causality
propensity-scores
causal-inference
uplift-modeling
counterfactual
causal-impact
propensity-score
uplift
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Mar 5, 2021 - Python
Code for the Recsys 2018 paper entitled Causal Embeddings for Recommandation.
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Oct 24, 2018 - Python
Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
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Mar 5, 2021 - Jupyter Notebook
DoubleML - Double Machine Learning in Python
python
data-science
machine-learning
statistics
scikit-learn
econometrics
causal-inference
double-machine-learning
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Jun 15, 2022 - Python
Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction
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Jun 17, 2021 - Python
A selection of state-of-the-art research materials on decision making and motion planning.
machine-learning
reinforcement-learning
deep-learning
algorithms
robotics
decision-making
motion-planning
artificial-intelligence
trajectory-generation
autonomous-vehicles
causal-inference
inverse-reinforcement-learning
intelligent-transportation-systems
trajectory-prediction
motion-control
multiagent-reinforcement-learning
multi-agent-learning
trajectory-planning
motion-prediction
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Aug 26, 2020
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chiragnagpal
commented
Oct 29, 2020
Currently we do not have notebooks that compare performance of DSM with other models.
We would need to compare against:
-DeepHit
-DeepSurv
-Random Survival Forest
-Cox PH
on Time Dependent CI and Brier Score.
documentation
Improvements or additions to documentation
help wanted
Extra attention is needed
good first issue
Good for newcomers
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3
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Dec 30, 2020 - Jupyter Notebook
This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.
conversations
emotion
inference
dataset
causality
natural-language-inference
causal-inference
dialogue-systems
reasoning
emotion-recognition
causal-models
dialogue-generation
roberta
bert-model
emotion-recognition-in-conversation
emotion-cause
emotion-cause-pair-extraction
emotion-tasks
causal-spans
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Apr 15, 2022 - Python
Causal inference, graphical models and structure learning with the PC algorithm.
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Jan 11, 2022 - Julia
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I've faced a problem that importing
dowhy.plotterlead to incorrect visual settings for all future rendered plots.It would be great to avoid overriding default matplotlib settings:
https://github.com/microsoft/dowhy/blob/master/dowhy/plotter.py#L7-L13
A possible solution is to encapsulate these settings into
dowhy.plotterfunctions instead of overriding global variables.