8 papers
Emputation: Identification-Guided Neural Imputation Framework
Yanjiao Yang, Yikun Zhang, Xinwei Shen +1
We propose Emputation, a deep generative framework for learning imputation models. Emputation targets the extrapolation distribution of missing variables given observed variables,…
A Practical Introduction to Regression-based Causal Inference in Meteorology (I): All confounders measured
Caren Marzban, Yikun Zhang, Nicholas Bond +1
Whether a variable is the cause of another, or simply associated with it, is often an important scientific question. Causal Inference is the name associated with the body of techni…
Transfer Learning Through Conditional Quantile Matching
Yikun Zhang, Steven Wilkins-Reeves, Wesley Lee +1
We introduce a transfer learning framework for regression that leverages heterogeneous source domains to improve predictive performance in a data-scarce target domain. Our approach…
BLADE: Benchmarking Language Model Agents for Data-Driven Science
Ken Gu, Ruoxi Shang, Ruien Jiang +13
Data-driven scientific discovery requires the iterative integration of scientific domain knowledge, statistical expertise, and an understanding of data semantics to make nuanced an…
Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach
Yikun Zhang, Yen-Chi Chen
The set of local modes and density ridge lines are important summary characteristics of the data-generating distribution. In this work, we focus on estimating local modes and densi…
Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments
Yikun Zhang, Yen-Chi Chen
Statistical methods for causal inference with continuous treatments mainly focus on estimating the mean potential outcome function, commonly known as the dose-response curve. Howev…