Possibility of using overrule to evaluate overlap in causal inference: What is the performance of overrule in identifying overlap for different types of datasets?

Machine Learning and Causal Inference for the estimation of the effect of tacrolimus on kidney rejections

Effectiveness of propensity score methods with density estimation in identifying overlap for causal inference

Using Nearest-Neighbors to Evaluate Overlap in Causal Inference

Empirical Investigation of Learning Curves: Assessing Convexity Characteristics

Non-Monotonicity in Empirical Learning Curves: Identifying non-monotonicity through slope approximations on discrete points

A Comparative Analysis of Learning Curve Models and their Applicability in Different Scenarios: Finding datasets patterns which lead to certain parametric curve model

An Empirical Study of Adaptive Kernel Density Estimation in Detecting Distributional Overlap

”How Much Data is Enough?” Learning curves for machine learning: Investigating alternatives to the Levenberg-Marquardt algorithm for learning curve extrapolation

Estimating the effect of ‘diverse’ team compositions on Dota 2 game outcomes using Inverse Probability Weighting

Understanding Risk Extrapolation (REx) and when it finds Invariant Relationships

Group Distributionally Robust Optimization for Solving Out-Of-Domain Generalization and Finding Causal Invariant Relationships

Causal Inference in DotA 2 when estimated through randomized data

Validating the win-rate of heroes in Dota 2 using instrumental variable estimation

Evaluating the Performance of the Model Selection with Average ECE and Naive Calibration in Out-of-Domain Generalization Problems for Binary Classifiers

Finding the causal effect of picking Slark in the game of Dota 2 on the final match outcome based on in-match events using the front-door adjustment

Discovering the effect of hero choice on the outcome of a Dota 2 game

Can Invariant Risk Minimization resist the temptation of learning spurious correlations?

An empirical study of the effects of unconfoundedness on the performance of Propensity Score Matching

Honesty in Causal Forests, is it worth it ?