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07/04/2023
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
Graph neural networks (GNNs) have become increasingly popular for classi...
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12/06/2022
ADIR: Adaptive Diffusion for Image Reconstruction
In recent years, denoising diffusion models have demonstrated outstandin...
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10/29/2022
Perturbation Analysis of Neural Collapse
Training deep neural networks for classification often includes minimizi...
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04/21/2022
Performance Analysis of Automotive SAR With Radar Based Motion Estimation
Automotive synthetic aperture radar (SAR) can achieve a significant angu...
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02/16/2022
Extended Unconstrained Features Model for Exploring Deep Neural Collapse
The modern strategy for training deep neural networks for classification...
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02/04/2021
Image Restoration by Deep Projected GSURE
Ill-posed inverse problems appear in many image processing applications,...
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01/27/2021
An Interpretation of Regularization by Denoising and its Application with the Back-Projected Fidelity Term
The vast majority of image recovery tasks are ill-posed problems. As suc...
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09/21/2020
Kernel-Based Smoothness Analysis of Residual Networks
A major factor in the success of deep neural networks is the use of soph...
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05/03/2020
On the Convergence Rate of Projected Gradient Descent for a Back-Projection based Objective
Ill-posed linear inverse problems appear in many fields of imaging scien...
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03/11/2020
BP-DIP: A Backprojection based Deep Image Prior
Deep neural networks are a very powerful tool for many computer vision t...
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11/30/2019
Correction Filter for Single Image Super-Resolution: Robustifying Off-the-Shelf Deep Super-Resolvers
The single image super-resolution task is one of the most examined inver...
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06/16/2019
Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems
Ill-posed linear inverse problems appear in many image processing applic...
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06/12/2019
Image-Adaptive GAN based Reconstruction
In the recent years, there has been a significant improvement in the qua...
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02/10/2019
Performance Advantages of Deep Neural Networks for Angle of Arrival Estimation
The problem of estimating the number of sources and their angles of arri...
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11/30/2018
Super-Resolution based on Image-Adapted CNN Denoisers: Incorporating Generalization of Training Data and Internal Learning in Test Time
While deep neural networks exhibit state-of-the-art results in the task ...
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10/18/2017
Image Restoration by Iterative Denoising and Backward Projections
Inverse problems appear in many applications such as image deblurring an...
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03/06/2017