Comparing effectiveness of the most common causal machine learning methods across various treatment effect, model complexities, data dimensions and sample sizes.
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Updated
Sep 8, 2023 - R
Comparing effectiveness of the most common causal machine learning methods across various treatment effect, model complexities, data dimensions and sample sizes.
This repo contains all replication files for my M.Sc thesis on "Machine Learning Methods to estimate treatment effects with multivalued treatment".
2023학년도 2학기 경기변동론 프로젝트 페이지
We perform market regime detection by testing three deep representation learning models tailored to the SPD Riemannian manifold of correlation matrices constructed from Bloomberg JSE Top 60 traded stock price returns data and synthetically-generated block hierarchical correlation matrices.
ImpactFlow is a Python Library for decision modeling based on causal decision models - in which levers and external factors of decisions feed into outcomes.
Code of diploma thesis "Study of Causal Machine Learning Techniques on Data from IoT Applications"
가짜연구소 <인과추론과 실무> 프로젝트
This is the public repository of the code implementation for KCRL.
An educational Python-based introduction to causal inference techniques using machine learning.
Causal Machine Learning project analyzing and evaluating different Double ML models for estimating treatment effects in observational data.
This library provides packages on DoubleML / Causal Machine Learning and Neural Networks in Python for Simulation and Case Studies.
Official PyTorch Implementation for "Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection" in CVPR 2024
scmopy: Distribution-Agnostic Structural Causal Models Optimization in Python
Taking causal inference to the extreme!
Causal Discovery with Prior Knowledge
Code for Causal GAIL. "Learning human driving behaviors with sequential causal imitation learning", AAAI-22.
Robust Smooth Heterogeneous Treatment Effect Estimation using Causal Machine Learning
Causal segmentation: estimating conditional average treatment effects for the heterogeneous groups in a sample
Explore the impact of discounts and tech support on revenue through Causal ML models. This repo provides an analysis notebook, data, and a guide on leveraging machine learning for strategic business decisions.
Treatment evaluation in presence of large number of covariates or treatment heterogeneity through Machine Learning methods
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