T2.R1.1
Towards Distribution-Shift Uncertainty Estimation for Inverse Problems with Generative Priors
Namhoon Kim, Sara Fridovich-Keil, Georgia Institute of Technology, United States
Session:
T2.R1: Exploiting Low-Dimensional Structures and Generative Models for Solving High-Dimensional Inverse Problems Lecture
Track:
Special Sessions
Location:
Isabela I
Presentation Time:
Tue, 16 Dec, 16:00 - 16:20 AST (UTC -4)
Session Co-Chairs:
Qing Qu, University of Michigan and Fauzia Ahmad, Temple University
Session T2.R1
T2.R1.1: Towards Distribution-Shift Uncertainty Estimation for Inverse Problems with Generative Priors
Namhoon Kim, Sara Fridovich-Keil, Georgia Institute of Technology, United States
T2.R1.2: Network-Regularized Diffusion Sampling For 3D Computed Tomography
Shijun Liang, Ismail Alkhouri, UMich and MSU, United States; Qing Qu, UMich, United States; Rongrong Wang, Saiprasad Ravishankar, MSU, United States
T2.R1.3: Flow with Interpolant Guidance for Linear Inverse Problems
Yici Yan, Yichi Zhang, University of Illinois Urbana-Champaign, United States; Xiangming Meng, ZJU-UIUC Institute, Zhejiang University, China; Zhizhen Zhao, University of Illinois Urbana-Champaign, United States
T2.R1.4: FMPLUG: PLUG-IN FOUNDATION FLOW-MATCHING PRIORS FOR INVERSE PROBLEMS
Yuxiang Wan, Ryan Devera, Wenjie Zhang, Ju Sun, University of Minnesota, United States
Contacts