45 citations · 135 across the 13 of their papers we have counts for
6 papers · 1 filter
Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models
Mohammad Shahab Sepehri, Zalan Fabian, Mahdi Soltanolkotabi
The landscape of computational building blocks of efficient image restoration architectures is dominated by a combination of convolutional processing and various attention mechanis…
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
Inverse problems arise in a multitude of applications, where the goal is to recover a clean signal from noisy and possibly (non)linear observations. The difficulty of a reconstruct…
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
Diffusion models have established new state of the art in a multitude of computer vision tasks, including image restoration. Diffusion-based inverse problem solvers generate recons…
HUMUS-Net: Hybrid unrolled multi-scale network architecture for accelerated MRI reconstruction
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
In accelerated MRI reconstruction, the anatomy of a patient is recovered from a set of under-sampled and noisy measurements. Deep learning approaches have been proven to be success…
Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
Deep neural networks have emerged as very successful tools for image restoration and reconstruction tasks. These networks are often trained end-to-end to directly reconstruct an im…
3D Phase Retrieval at Nano-Scale via Accelerated Wirtinger Flow
Zalan Fabian, Justin Haldar, Richard Leahy +1
Imaging 3D nano-structures at very high resolution is crucial in a variety of scientific fields. However, due to fundamental limitations of light propagation we can only measure th…