Следене
Davis Gilton
Davis Gilton
Потвърден имейл адрес: microsoft.com
Заглавие
Позовавания
Позовавания
Година
Deep equilibrium architectures for inverse problems in imaging
D Gilton, G Ongie, R Willett
IEEE Transactions on Computational Imaging 7, 1123-1133, 2021
1642021
Neumann networks for linear inverse problems in imaging
D Gilton, G Ongie, R Willett
IEEE Transactions on Computational Imaging 6, 328-343, 2019
1532019
Model adaptation for inverse problems in imaging
D Gilton, G Ongie, R Willett
IEEE Transactions on Computational Imaging 7, 661-674, 2021
522021
Sparse linear contextual bandits via relevance vector machines
D Gilton, R Willett
2017 International Conference on Sampling Theory and Applications (SampTA …, 2017
172017
Data-driven cloud clustering via a rotationally invariant autoencoder
T Kurihana, E Moyer, R Willett, D Gilton, I Foster
IEEE Transactions on Geoscience and Remote Sensing 60, 1-25, 2021
142021
Learned patch-based regularization for inverse problems in imaging
D Gilton, G Ongie, R Willett
2019 ieee 8th international workshop on computational advances in multi …, 2019
112019
Masked LARk: Masked learning, aggregation and reporting workflow
JJ Pfeiffer III, D Charles, D Gilton, YH Jung, M Parsana, E Anderson
arXiv preprint arXiv:2110.14794, 2021
92021
Detection and description of change in visual streams
D Gilton, R Luo, R Willett, G Shakhnarovich
arXiv preprint arXiv:2003.12633, 2020
52020
Adaptive Off-ramp Training and Inference for Early Exits in a Deep Neural Network
SKPKM Naga, JJ Pfeiffer III, DL Gilton
US Patent App. 17/348,299, 2022
12022
Model adaptation in biomedical image reconstruction
D Gilton, G Ongie, R Willett
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1223-1226, 2021
12021
Learning to solve linear inverse problems in imaging with Neumann networks
G Ongie, D Gilton, R Willett
NeurIPS 2019 Workshop on Solving Inverse Problems with Deep Networks, 2019
12019
Learning to Regularize Using Neumann Networks
D Gilton, G Ongie, R Willett
2019 IEEE Data Science Workshop (DSW), 201-207, 2019
12019
Cloud Clustering Applied to MODIS Calibrated Radiances Over 2003 via Rotationally Invariant Autoencoder
T Kurihana, E Moyer, R Willett, D Gilton, I Foster
AGU Fall Meeting Abstracts 2021, A35C-1635, 2021
2021
Cloud Clustering Over January 2003 via Scalable Rotationally Invariant Autoencoder
T Kurihana, E Moyer, R Willett, D Gilton, I Foster
2021 IEEE 17th International Conference on eScience (eScience), 253-254, 2021
2021
Learning Robust Data-Driven Methods for Inverse Problems and Change Detection
D Gilton
The University of Wisconsin-Madison, 2021
2021
Neumann networks for inverse problems in imaging
D Gilton, G Ongie, R Willett
arXiv preprint arXiv:1901.03707, 2019
2019
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