| Deep learning for inverse problems: Bounds and regularizers J Amjad, Z Lyu, MRD Rodrigues arXiv preprint arXiv:1901.11352, 2019 | 8 | 2019 |
| Deep learning model-aware regulatization with applications to inverse problems J Amjad, Z Lyu, MRD Rodrigues IEEE Transactions on Signal Processing 69, 6371-6385, 2021 | 7 | 2021 |
| Regression with deep neural networks: generalization error guarantees, learning algorithms, and regularizers J Amjad, Z Lyu, MRD Rodrigues 2021 29th European Signal Processing Conference (EUSIPCO), 1481-1485, 2021 | 3 | 2021 |
| A Popularity-and Mobility-Aware Multi-layer Caching with Feedback Mechanism for Highway Vehicular Networks K Li, Z Lyu, H Liu, P Fan 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), 1-6, 2020 | 2 | 2020 |
| Model-aware regularization for learning approaches to inverse problems J Amjad, Z Lyu, MRD Rodrigues arXiv preprint arXiv:2006.10869, 2020 | 1 | 2020 |
| BITS-Net: Blind Image Transparency Separation Network C Zhou, Z Lyu, MRD Rodrigues 2023 IEEE International Conference on Image Processing (ICIP), 375-379, 2023 | | 2023 |
| On Neural Networks Fitting, Compression, and Generalization Behavior via Information-Bottleneck-like Approaches Z Lyu, G Aminian, MRD Rodrigues Entropy 25 (7), 1063, 2023 | | 2023 |
| Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck Z Lyu, G Aminian, MRD Rodrigues 2021 IEEE 31st International Workshop on Machine Learning for Signal …, 2021 | | 2021 |
| Synthetic Labeling: A Novel Approach to Advancing Few-Shot Learning Z Lyu, G Aminian, MRD Rodrigues The Second Tiny Papers Track at ICLR 2024, 0 | | |
