Preliminary approach to estimation and prediction of infrared spectroscopy for Mannich bases by atomic electronegativity distance vector (VAED). - Chunyang Liao; Zhitao Chen; Zihui Yin; Shengshi Z. Li (Comput. Biol. Chem., 2003)

Learning from Non-IID Data in Hilbert Spaces: An Optimal Recovery Perspective. - Simon Foucart; Chunyang Liao; Shahin Shahrampour; Yinsong Wang (CoRR, 2020)

Optimal Recovery from Inaccurate Data in Hilbert Spaces: Regularize, but what of the Parameter? - Simon Foucart; Chunyang Liao (CoRR, 2021)

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. - Mingrui Liu; Zhenxun Zhuang; Yunwen Lei; Chunyang Liao (NeurIPS, 2022)

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. - Mingrui Liu; Zhenxun Zhuang; Yunwei Lei; Chunyang Liao (CoRR, 2022)

On the Optimal Recovery of Graph Signals. - Simon Foucart; Chunyang Liao; Nate Veldt (CoRR, 2023)

S-Procedure Relaxation: a Case of Exactness Involving Chebyshev Centers. - Simon Foucart; Chunyang Liao (CoRR, 2023)

Differentially Private Random Feature Model. - Chunyang Liao; Deanna Needell; Alexander Xue (CoRR, 2024)

Radius of information for two intersected centered hyperellipsoids and implications in optimal recovery from inaccurate data. - Simon Foucart; Chunyang Liao (J. Complex., 2024)

Solving Partial Differential Equations with Random Feature Models. - Chunyang Liao (CoRR, 2025)

Cauchy Random Features for Operator Learning in Sobolev Space. - Chunyang Liao; Deanna Needell; Hayden Schaeffer (CoRR, 2025)