Jiahe Lin

According to our database, Jiahe Lin authored at least 14 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Covariate-dependent Graphical Model Estimation via Neural Networks with Statistical Guarantees.

Jiahe Lin, Yikai Zhang, George Michailidis

Trans. Mach. Learn. Res., 2025

Reweighting Improves Conditional Risk Bounds.

Yikai Zhang, Jiahe Lin, Fengpei Li, Songzhu Zheng, Anant Raj, Anderson Schneider, Yuriy Nevmyvaka

Trans. Mach. Learn. Res., 2025

Whisk: Inducing Altruistic Behavior to Relieve Child Dental Anxiety.

Shuzi Yin, Bingjie Gao, Rui Zhang, Jiahe Lin, Yeonsu Shin, Yijie Guo, Haipeng Mi

Proceedings of the 20th ACM/IEEE International Conference on Human-Robot Interaction, 2025

2024

A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity.

Jiahe Lin, Huitian Lei, George Michailidis

Trans. Mach. Learn. Res., 2024

Structural Discovery with Partial Ordering Information for Time-Dependent Data with Convergence Guarantees.

Jiahe Lin, Huitian Lei, George Michailidis

J. Comput. Graph. Stat., 2024

Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate.

Fengpei Li, Haoxian Chen, Jiahe Lin, Arkin Gupta, Xiaowei Tan, Gang Xu, Yuriy Nevmyvaka, Agostino Capponi, Henry Lam

CoRR, 2024

Deep Learning-based Approaches for State Space Models: A Selective Review.

Jiahe Lin, George Michailidis

CoRR, 2024

2023

"Kaleidoscope Eyes": The Exploration of a Sense of Place Through Art Strolling in Mozilla Hubs.

Jiahe Lin

Int. J. Emerg. Technol. Learn., May, 2023

Risk Bounds on Aleatoric Uncertainty Recovery.

Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Nonlinear modeling and prediction of forklift acoustic annoyance based on the improved neural networks.

Enlai Zhang, Jiading Lian, Jingjing Zhang, Jiahe Lin

Simul., 2022

2020

System Identification of High-Dimensional Linear Dynamical Systems With Serially Correlated Output Noise Components.

Jiahe Lin, George Michailidis

IEEE Trans. Signal Process., 2020

Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models.

Jiahe Lin, George Michailidis

J. Mach. Learn. Res., 2020

2017

Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models.

Jiahe Lin, George Michailidis

J. Mach. Learn. Res., 2017

2016

Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models.

Jiahe Lin, Sumanta Basu, Moulinath Banerjee, George Michailidis

J. Mach. Learn. Res., 2016