15 papers
Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
Cheng-Han Huang, Yongliang Sun, Chaoyan Huang +2
Many combinatorial optimization problems admit quadratic unconstrained binary formulations (QUBO) which can often be relaxed to the box and optimized using scalable gradi…
ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing
Yixuan Jia, Siyi Chen, Yida Pan +9
Data assimilation (DA) estimates the state of an evolving dynamical system from noisy, partial observations, and is widely used in scientific simulation as well as weather and clim…
A Principled Self-Referenced Early Stopping Approach for Deep Image Prior
Chaoyan Huang, Cheng-Han Huang, Ismail R. Alkhouri +1
Recently, Deep Image Prior (DIP) has demonstrated strong capabilities for solving inverse imaging problems (IIPs) by optimizing a randomly initialized convolutional neural network…
Dynamic MRI Reconstruction Via Dual Deep Priors and Low-Rank Plus Sparse Modeling
Yongliang Sun, Siddhant Gautam, Chaoyan Huang +3
Dynamic MRI reconstruction from undersampled measurements is a challenging inverse problem that requires preserving both spatial reconstruction quality and temporal consistency acr…
Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures
Huijie Zhang, Yifu Lu, Ismail Alkhouri +3
Diffusion models, emerging as powerful deep generative tools, excel in various applications. They operate through a two-steps process: introducing noise into training samples and t…
Tada-DIP: Input-adaptive Deep Image Prior for One-shot 3D Image Reconstruction
Evan Bell, Shijun Liang, Ismail Alkhouri +1
Deep Image Prior (DIP) has recently emerged as a promising one-shot neural-network based image reconstruction method. However, DIP has seen limited application to 3D image reconstr…