4 citations · 4 across the 10 of their papers we have counts for
11 papers
Diffusion Based Unpaired Data Learning for Inverse Problems
Chenglong Bao, Yiming Dang, Chenguang Duan +2
Data is important in many deep learning-based inverse problem solvers. However, obtaining sufficient paired data in many scenarios remains highly challenging, while unpaired data i…
Addressing preferred orientation in single-particle cryo-EM through AI-generated auxiliary particles
Hui Zhang, Dihan Zheng, Qiurong Wu +4
The single-particle cryo-EM field faces the persistent challenge of preferred orientation, lacking general computational solutions. We introduce cryoPROS, an AI-based approach desi…
The Global R-linear Convergence of Nesterov's Accelerated Gradient Method with Unknown Strongly Convex Parameter
Chenglong Bao, Liang Chen, Jiahong Li
The Nesterov accelerated gradient (NAG) method is an important extrapolation-based numerical algorithm that accelerates the convergence of the gradient descent method in convex opt…
Convergence Analysis for Restarted Anderson Mixing and Beyond
Fuchao Wei, Chenglong Bao, Yang Liu +1
Anderson mixing (AM) is a classical method that can accelerate fixed-point iterations by exploring historical information. Despite the successful application of AM in scientific co…
Averaging Orientations with Molecular Symmetry in Cryo-EM
Qi Zhang, Chenglong Bao, Hai Lin +1
Cryogenic electron microscopy (cryo-EM) is an invaluable technique for determining high-resolution three-dimensional structures of biological macromolecules using transmission part…
On the robust isolated calmness of a class of nonsmooth optimizations on Riemannian manifolds and its applications
Chenglong Bao, Chao Ding, Yuexin Zhou
This paper studies the robust isolated calmness property of the KKT solution mapping of a class of nonsmooth optimization problems on Riemannian manifolds. The manifold versions of…