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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 ...
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08/03/2021
Robust Compressed Sensing MRI with Deep Generative Priors
The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep gen...
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06/23/2021
Fairness for Image Generation with Uncertain Sensitive Attributes
This work tackles the issue of fairness in the context of generative pro...
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06/21/2021
Instance-Optimal Compressed Sensing via Posterior Sampling
We characterize the measurement complexity of compressed sensing of sign...
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02/15/2021
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
We propose Intermediate Layer Optimization (ILO), a novel optimization a...
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06/16/2020
Robust compressed sensing of generative models
The goal of compressed sensing is to estimate a high dimensional vector ...
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05/12/2020
Deep Learning Techniques for Inverse Problems in Imaging
Recent work in machine learning shows that deep neural networks can be u...
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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...
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06/17/2018
Compressed Sensing with Deep Image Prior and Learned Regularization
We propose a novel method for compressed sensing recovery using untraine...
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12/26/2017
The Robust Manifold Defense: Adversarial Training using Generative Models
Deep neural networks are demonstrating excellent performance on several ...
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03/09/2017