Wei Zhu
Wei Zhu
Assistant Professor, School of Mathematics, Georgia Institute of Technology
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Citado por
Citado por
Low dimensional manifold model for image processing
S Osher, Z Shi, W Zhu
SIAM Journal on Imaging Sciences 10 (4), 1669-1690, 2017
Weighted nonlocal laplacian on interpolation from sparse data
Z Shi, S Osher, W Zhu
Journal of Scientific Computing 73, 1164-1177, 2017
Hyperspectral anomaly detection via global and local joint modeling of background
Z Wu, W Zhu, J Chanussot, Y Xu, S Osher
IEEE Transactions on Signal Processing 67 (14), 3858-3869, 2019
Unsupervised classification in hyperspectral imagery with nonlocal total variation and primal-dual hybrid gradient algorithm
W Zhu, V Chayes, A Tiard, S Sanchez, D Dahlberg, AL Bertozzi, S Osher, ...
IEEE Transactions on Geoscience and Remote Sensing 55 (5), 2786-2798, 2017
LDMNet: Low dimensional manifold regularized neural networks
W Zhu, Q Qiu, J Huang, R Calderbank, G Sapiro, I Daubechies
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Deep neural nets with interpolating function as output activation
B Wang, X Luo, Z Li, W Zhu, Z Shi, S Osher
Advances in neural information processing systems 31, 2018
Scaling-translation-equivariant networks with decomposed convolutional filters
W Zhu, Q Qiu, R Calderbank, G Sapiro, X Cheng
Journal of machine learning research 23 (68), 1-45, 2022
Adversarial defense via data dependent activation function and total variation minimization
B Wang, AT Lin, W Zhu, P Yin, AL Bertozzi, SJ Osher
arXiv preprint arXiv:1809.08516, 2018
Generalization of the weighted nonlocal laplacian in low dimensional manifold model
Z Shi, S Osher, W Zhu
Journal of Scientific Computing 75, 638-656, 2018
Scalable low dimensional manifold model in the reconstruction of noisy and incomplete hyperspectral images
W Zhu, Z Shi, S Osher
2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2018
Scientific data interpolation with low dimensional manifold model
W Zhu, B Wang, R Barnard, CD Hauck, F Jenko, S Osher
Journal of Computational Physics 352, 213-245, 2018
Neural networks enforcing physical symmetries in nonlinear dynamical lattices: The case example of the Ablowitz–Ladik model
W Zhu, W Khademi, EG Charalampidis, PG Kevrekidis
Physica D: Nonlinear Phenomena 434, 133264, 2022
Structure-preserving GANs
J Birrell, M Katsoulakis, L Rey-Bellet, W Zhu
International Conference on Machine Learning 162, 1982-2020, 2022
Deformation robust roto-scale-translation equivariant CNNs
L Gao, G Lin, W Zhu
arXiv preprint arXiv:2111.10978, 2021
Low dimensional manifold model with semi-local patches
Z Shi, S Osher, W Zhu
UCLA CAM Report (16–63), 2016
Adversarial defense via the data-dependent activation, total variation minimization, and adversarial training
B Wang, A Lin, P Yin, W Zhu, A L Bertozzi, S J Osher
Inverse Problems & Imaging, 2020
Deep learning with data dependent implicit activation function
B Wang, X Luo, Z Li, W Zhu, Z Shi, SJ Osher
CoRR, abs/1802.00168, 2018
Discovering governing equations in discrete systems using pinns
S Saqlain, W Zhu, EG Charalampidis, PG Kevrekidis
Communications in Nonlinear Science and Numerical Simulation 126, 107498, 2023
Sample complexity of probability divergences under group symmetry
Z Chen, M Katsoulakis, L Rey-Bellet, W Zhu
International Conference on Machine Learning, 4713-4734, 2023
Stop memorizing: A data-dependent regularization framework for intrinsic pattern learning
W Zhu, Q Qiu, B Wang, J Lu, G Sapiro, I Daubechies
SIAM Journal on Mathematics of Data Science 1 (3), 476-496, 2019
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
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