Deep Learning for Inverse Problems: Bounds and Regularizers. - Jaweria Amjad; Zhaoyan Lyu; Miguel R. D. Rodrigues (CoRR, 2019)

A Popularity- and Mobility-Aware Multi-layer Caching with Feedback Mechanism for Highway Vehicular Networks. - Ke Li 020; Zhaoyan Lyu; Heng Liu 009; Pingzhi Fan (VTC Fall, 2020)

Model-Aware Regularization For Learning Approaches To Inverse Problems. - Jaweria Amjad; Zhaoyan Lyu; Miguel R. D. Rodrigues (CoRR, 2020)

Regression with Deep Neural Networks: Generalization Error Guarantees, Learning Algorithms, and Regularizers. - Jaweria Amjad; Zhaoyan Lyu; Miguel R. D. Rodrigues (EUSIPCO, 2021)

Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck. - Zhaoyan Lyu; Gholamali Aminian; Miguel R. D. Rodrigues (MLSP, 2021)

Deep Learning Model-Aware Regulatization With Applications to Inverse Problems. - Jaweria Amjad; Zhaoyan Lyu; Miguel R. D. Rodrigues (IEEE Trans. Signal Process., 2021)

BITS-Net: Blind Image Transparency Separation Network. - Chao Zhou; Zhaoyan Lyu; Miguel R. D. Rodrigues (ICIP, 2023)

On Neural Networks Fitting, Compression, and Generalization Behavior via Information-Bottleneck-like Approaches. - Zhaoyan Lyu; Gholamali Aminian; Miguel R. D. Rodrigues (Entropy, 2023)

Synthetic Labeling: A Novel Approach to Advancing Few-Shot Learning. - Zhaoyan Lyu; Gholamali Aminian; Miguel R. D. Rodrigues (Tiny Papers @ ICLR, 2024)