Learned Patch-Based Regularization for Inverse Problems in Imaging. - Davis Gilton; Greg Ongie; Rebecca Willett (CAMSAP, 2019)

Learning to Regularize Using Neumann Networks. - Davis Gilton; Greg Ongie; Rebecca Willett (DSW, 2019)

Neumann Networks for Inverse Problems in Imaging. - Davis Gilton; Greg Ongie; Rebecca Willett (CoRR, 2019)

Detection and Description of Change in Visual Streams. - Davis Gilton; Ruotian Luo; Rebecca Willett; Greg Shakhnarovich (CoRR, 2020)

Neumann Networks for Linear Inverse Problems in Imaging. - Davis Gilton; Greg Ongie; Rebecca Willett (IEEE Trans. Computational Imaging, 2020)

Cloud Clustering Over January 2003 via Scalable Rotationally Invariant Autoencoder. - Takuya Kurihana; Elisabeth Moyer; Rebecca Willett; Davis Gilton; Ian T. Foster (e-Science, 2021)

Model Adaptation In Biomedical Image Reconstruction. - Davis Gilton; Greg Ongie; Rebecca Willett (ISBI, 2021)

Masked LARk: Masked Learning, Aggregation and Reporting worKflow. - Joseph J. Pfeiffer III; Denis Charles; Davis Gilton; Young Hun Jung; Mehul Parsana; Erik Anderson (CoRR, 2021)

Model Adaptation for Inverse Problems in Imaging. - Davis Gilton; Gregory Ongie; Rebecca Willett (IEEE Trans. Computational Imaging, 2021)

Deep Equilibrium Architectures for Inverse Problems in Imaging. - Davis Gilton; Gregory Ongie; Rebecca Willett (IEEE Trans. Computational Imaging, 2021)

Data-Driven Cloud Clustering via a Rotationally Invariant Autoencoder. - Takuya Kurihana; Elisabeth Moyer; Rebecca Willett; Davis Gilton; Ian T. Foster (IEEE Trans. Geosci. Remote. Sens., 2022)