Lin, Jiahe

7 publications

TMLR 2025 Covariate-Dependent Graphical Model Estimation via Neural Networks with Statistical Guarantees Jiahe Lin, Yikai Zhang, George Michailidis

TMLR 2025 Reweighting Improves Conditional Risk Bounds Yikai Zhang, Jiahe Lin, Fengpei Li, Songzhu Zheng, Anant Raj, Anderson Schneider, Yuriy Nevmyvaka

TMLR 2024 A VAE-Based Framework for Learning Multi-Level Neural Granger-Causal Connectivity Jiahe Lin, Huitian Lei, George Michailidis

AISTATS 2023 Risk Bounds on Aleatoric Uncertainty Recovery Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka

JMLR 2020 Regularized Estimation of High-Dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models Jiahe Lin, George Michailidis

JMLR 2017 Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models Jiahe Lin, George Michailidis

JMLR 2016 Penalized Maximum Likelihood Estimation of Multi-Layered Gaussian Graphical Models Jiahe Lin, Sumanta Basu, Moulinath Banerjee, George Michailidis