Platonic Representations for Poverty Mapping: Unified Vision-Language Codes or Agent-Induced Novelty? Paper • 2508.01109 • Published Aug 1 • 3
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis Paper • 2508.01341 • Published Aug 2 • 1
Benchmarking Debiasing Methods for LLM-based Parameter Estimates Paper • 2506.09627 • Published Jun 11 • 1
Selecting Optimal Candidate Profiles in Adversarial Environments Using Conjoint Analysis and Machine Learning Paper • 2504.19043 • Published Apr 26 • 4
fastrerandomize: An R Package for Fast Rerandomization Using Accelerated Computing Paper • 2501.07642 • Published Jan 13
Encoding Multi-level Dynamics in Effect Heterogeneity Estimation Paper • 2411.02134 • Published Nov 4, 2024
Effect Heterogeneity with Earth Observation in Randomized Controlled Trials: Exploring the Role of Data, Model, and Evaluation Metric Choice Paper • 2407.11674 • Published Jul 16, 2024
Planetary Causal Inference: Implications for the Geography of Poverty Paper • 2406.02584 • Published May 30, 2024
CausalImages: An R Package for Causal Inference with Earth Observation, Bio-medical, and Social Science Images Paper • 2310.00233 • Published Sep 30, 2023
Linking Datasets on Organizations Using Half A Billion Open Collaborated Records Paper • 2302.02533 • Published Feb 6, 2023
Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities Paper • 2301.12985 • Published Jan 30, 2023