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Difan Zou
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Cited by
Year
Gradient descent optimizes over-parameterized deep ReLU networks
D Zou, Y Cao, D Zhou, Q Gu
Machine learning 109, 467-492, 2020
6902020
Improving adversarial robustness requires revisiting misclassified examples
Y Wang, D Zou, J Yi, J Bailey, X Ma, Q Gu
International conference on learning representations, 2019
6442019
Layer-dependent importance sampling for training deep and large graph convolutional networks
D Zou, Z Hu, Y Wang, S Jiang, Y Sun, Q Gu
Advances in neural information processing systems 32, 2019
2752019
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ...
Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022
240*2022
An improved analysis of training over-parameterized deep neural networks
D Zou, Q Gu
NeurIPS 2018, 2019
2292019
Global convergence of Langevin dynamics based algorithms for nonconvex optimization
P Xu, J Chen, D Zou, Q Gu
Advances in Neural Information Processing Systems 31, 2018
2042018
Ensemble forecasts of coronavirus disease 2019 (COVID-19) in the US
EL Ray, N Wattanachit, J Niemi, AH Kanji, K House, EY Cramer, J Bracher, ...
MedRXiv, 2020.08. 19.20177493, 2020
1982020
How much over-parameterization is sufficient to learn deep ReLU networks?
Z Chen, Y Cao, D Zou, Q Gu
arXiv preprint arXiv:1911.12360, 2019
1262019
Epidemic model guided machine learning for COVID-19 forecasts in the United States
D Zou, L Wang, P Xu, J Chen, W Zhang, Q Gu
MedRxiv, 2020.05. 24.20111989, 2020
1132020
The United States COVID-19 forecast hub dataset
EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ...
Scientific data 9 (1), 462, 2022
772022
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave
J Bracher, D Wolffram, J Deuschel, K Görgen, JL Ketterer, A Ullrich, ...
Nature communications 12 (1), 5173, 2021
75*2021
A 1Mbps real-time NLOS UV scattering communication system with receiver diversity over 1km
G Wang, K Wang, C Gong, D Zou, Z Jiang, Z Xu
IEEE Photonics Journal 10 (2), 1-13, 2018
602018
Benign overfitting of constant-stepsize sgd for linear regression
D Zou, J Wu, V Braverman, Q Gu, S Kakade
Conference on Learning Theory, 4633-4635, 2021
572021
Information security risks outside the laser beam in terrestrial free-space optical communication
D Zou, Z Xu
IEEE Photonics Journal 8 (5), 1-9, 2016
532016
Characterization on practical photon counting receiver in optical scattering communication
D Zou, C Gong, K Wang, Z Xu
IEEE Transactions on Communications 67 (3), 2203-2217, 2018
452018
Multiple models for outbreak decision support in the face of uncertainty
K Shea, RK Borchering, WJM Probert, E Howerton, TL Bogich, SL Li, ...
Proceedings of the National Academy of Sciences 120 (18), e2207537120, 2023
40*2023
Stochastic variance-reduced hamilton monte carlo methods
D Zou, P Xu, Q Gu
International Conference on Machine Learning, 6028-6037, 2018
382018
Non-line-of-sight scattering channel modeling for underwater optical wireless communication
W Liu, D Zou, Z Xu, J Yu
2015 IEEE International Conference on Cyber Technology in Automation …, 2015
382015
Faster convergence of stochastic gradient langevin dynamics for non-log-concave sampling
D Zou, P Xu, Q Gu
Uncertainty in Artificial Intelligence, 1152-1162, 2021
372021
On the global convergence of training deep linear ResNets
D Zou, PM Long, Q Gu
arXiv preprint arXiv:2003.01094, 2020
342020
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Articles 1–20