1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Deconfounding via Profiled Transfer Learning
Ziyuan Chen, Yifan Jiang, Jingyuan Liu +1
Unmeasured confounders are a major source of bias in regression-based effect estimation and causal inference. In this paper, we propose a new profiled transfer learning framework,…
Deep Semiparametric Partial Differential Equation Models
Ziyuan Chen, Shunxing Yan, Fang Yao
In many scientific fields, the generation and evolution of data are governed by partial differential equations (PDEs) which are typically informed by established physical laws at t…
Semiparametric M-estimation with overparameterized neural networks
Shunxing Yan, Ziyuan Chen, Fang Yao
We focus on semiparametric regression that has played a central role in statistics, and exploit the powerful learning ability of deep neural networks (DNNs) while enabling statisti…
Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrapping
Pu Yang, Yunzhen Feng, Ziyuan Chen +2
Modern foundation models often undergo iterative ``bootstrapping'' in their post-training phase: a model generates synthetic data, an external verifier filters out low-quality samp…