Exploring modern machine learning methods to improve causal-effect estimation

Mathematics

• Causal Effect 100%
• Machine Learning 83%
• Causal Inference 68%
• Treatment Effects 54%
• Random Forest 36%
• Simple Linear Regression 33%
• Observational Study 32%
• Gold 31%
• Confounding 31%
• Learning Algorithm 29%
• Safety 28%
• Simulation Experiment 28%
• Training 26%
• Statistical Model 24%
• Maximum Likelihood Estimation 23%
• Scenarios 23%
• Covariates 21%
• Regression Model 20%
• Regression 19%
• Design 15%
• Context 15%
• Relationships 15%
• Estimator 15%
• Performance 15%
• Standards 13%
• Estimate 11%

Business & Economics

• Machine Learning 99%
• Learning Methods 94%
• Causal Effect 78%
• Causal Inference 65%
• Treatment Effects 56%
• Maximum Likelihood Estimation 46%
• Observational Study 33%
• Gold Standard 31%
• Learning Algorithm 30%
• Confounding 28%
• Simulation Experiment 27%
• Finite Sample 27%
• Linear Regression 26%
• Covariates 25%
• Safety 23%
• Regression Model 20%
• Estimator 20%
• Scenarios 16%
• Performance 9%

Engineering & Materials Science

• Machine learning 55%
• Maximum likelihood estimation 29%
• Random forests 26%
• Linear regression 25%
• Learning algorithms 20%
• Experiments 8%