activity
20192021
most citedNeumann Networks for Inverse Problems in Imaging

19 citations · 25 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CR20212 cited

Masked LARk: Masked Learning, Aggregation and Reporting worKflow

Joseph J. Pfeiffer, Denis Charles, Davis Gilton +3

Today, many web advertising data flows involve passive cross-site tracking of users. Enabling such a mechanism through the usage of third party tracking cookies (3PC) exposes sensi…

cs.CV2021

Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder

Takuya Kurihana, Elisabeth Moyer, Rebecca Willett +2

Advanced satellite-born remote sensing instruments produce high-resolution multi-spectral data for much of the globe at a daily cadence. These datasets open up the possibility of i…

eess.IV2021

Deep Equilibrium Architectures for Inverse Problems in Imaging

Davis Gilton, Gregory Ongie, Rebecca Willett

Recent efforts on solving inverse problems in imaging via deep neural networks use architectures inspired by a fixed number of iterations of an optimization method. The number of i…

eess.IV2020

Model Adaptation for Inverse Problems in Imaging

Davis Gilton, Gregory Ongie, Rebecca Willett

Deep neural networks have been applied successfully to a wide variety of inverse problems arising in computational imaging. These networks are typically trained using a forward mod…

cs.CV20204 cited

Detection and Description of Change in Visual Streams

Davis Gilton, Ruotian Luo, Rebecca Willett +1

This paper presents a framework for the analysis of changes in visual streams: ordered sequences of images, possibly separated by significant time gaps. We propose a new approach t…

cs.CV201919 cited

Neumann Networks for Inverse Problems in Imaging

Davis Gilton, Greg Ongie, Rebecca Willett

Many challenging image processing tasks can be described by an ill-posed linear inverse problem: deblurring, deconvolution, inpainting, compressed sensing, and superresolution all…