Ajil Jalal | DeepAI

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∙ 06/05/2023

Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models

Diffusion-based generative models have been used as powerful priors for ...

0 Sriram Ravula, et al. ∙

∙ 08/03/2021

Robust Compressed Sensing MRI with Deep Generative Priors

The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep gen...

15 Ajil Jalal, et al. ∙

∙ 06/23/2021

Fairness for Image Generation with Uncertain Sensitive Attributes

This work tackles the issue of fairness in the context of generative pro...

0 Ajil Jalal, et al. ∙

∙ 06/21/2021

Instance-Optimal Compressed Sensing via Posterior Sampling

We characterize the measurement complexity of compressed sensing of sign...

6 Ajil Jalal, et al. ∙

∙ 02/15/2021

Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

We propose Intermediate Layer Optimization (ILO), a novel optimization a...

13 Giannis Daras, et al. ∙

∙ 06/16/2020

Robust compressed sensing of generative models

The goal of compressed sensing is to estimate a high dimensional vector ...

4 Ajil Jalal, et al. ∙

∙ 05/12/2020

Deep Learning Techniques for Inverse Problems in Imaging

Recent work in machine learning shows that deep neural networks can be u...

11 Gregory Ongie, et al. ∙

∙ 06/18/2019

Inverting Deep Generative models, One layer at a time

We study the problem of inverting a deep generative model with ReLU acti...

23 Qi Lei, et al. ∙

∙ 06/17/2018

Compressed Sensing with Deep Image Prior and Learned Regularization

We propose a novel method for compressed sensing recovery using untraine...

10 David Van Veen, et al. ∙

∙ 12/26/2017

The Robust Manifold Defense: Adversarial Training using Generative Models

Deep neural networks are demonstrating excellent performance on several ...

0 Andrew Ilyas, et al. ∙

∙ 03/09/2017

Compressed Sensing using Generative Models

The goal of compressed sensing is to estimate a vector from an underdete...

0 Ashish Bora, et al. ∙

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