research
∙
07/04/2023
A Double Machine Learning Approach to Combining Experimental and Observational Data
Experimental and observational studies often lack validity due to untest...
share
research
∙
07/03/2023
Multi-Task Learning Improves Performance In Deep Argument Mining Models
The successful analysis of argumentative techniques from user-generated ...
research
∙
04/03/2023
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics
We introduce Matched Machine Learning, a framework that combines the fle...
research
∙
11/23/2021
Measurement That Matches Theory: Theory-Driven Identification in IRT Models
Measurement bridges theory and empirics. Without measures that appropria...
research
∙
01/06/2021
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference
dame-flame is a Python package for performing matching for observational...
research
∙
09/06/2020
Matching Bounds: How Choice of Matching Algorithm Impacts Treatment Effects Estimates and What to Do about It
Different matches on the same data may produce different treatment effec...
research
∙
03/03/2020
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation
We propose a matching method for observational data that matches units w...
research
∙
03/02/2020
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference
We propose a matching method that recovers direct treatment effects from...
research
∙
06/27/2019
Interpretable Almost-Matching-Exactly With Instrumental Variables
Uncertainty in the estimation of the causal effect in observational stud...
research
∙
12/05/2018