Li, Nan

CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding

Lanusse, F., Ma, Q., Li, N., Collett, T. E., Li, C.-L., Ravanbakhsh, S., Mandelbaum, R., & Póczos, B. (2018) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 191

The strong gravitational lens finding challenge

Metcalf, R. B., Meneghetti, M., Avestruz, C., Bellagamba, F., Bom, C. R., Bertin, E., Cabanac, R., Courbin, F., Davies, A., Decencière, E., et al. (2019) · Astronomy & Astrophysics

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 152

Open Category Classification by Adversarial Sample Generation

Yu, Y., Qu, W.-Y., Li, N., & Guo, Z. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

Adversarial Robustness in Machine LearningDomain Adaptation and Few-Shot Learning

Cited by 84

Federated Learning Empowered Real-Time Medical Data Processing Method for Smart Healthcare

Guo, K., Chen, T., Ren, S., Li, N., Hu, M., & Kang, J. (2024) · IEEE/ACM Transactions on Computational Biology and Bioinformatics

Privacy-Preserving Technologies in DataData Stream Mining Techniques

Cited by 63

Strong lens modelling: comparing and combining Bayesian neural networks and parametric profile fitting

Pearson, J., Maresca, J., Li, N., & Dye, S. (2021) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 31