Rgp: Neural network pruning through regular graph with edges swapping Z Chen, J Xiang, Y Lu, Q Xuan, Z Wang, G Chen, X Yang IEEE Transactions on Neural Networks and Learning Systems, 2023 | 15 | 2023 |
Understanding the dynamics of dnns using graph modularity Y Lu, W Yang, Y Zhang, Z Chen, J Chen, Q Xuan, Z Wang, X Yang European Conference on Computer Vision, 225-242, 2022 | 6 | 2022 |
Sr-init: An interpretable layer pruning method H Tang, Y Lu, Q Xuan ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 5 | 2023 |
Can pre-trained models assist in dataset distillation? Y Lu, X Chen, Y Zhang, J Gu, T Zhang, Y Zhang, X Yang, Q Xuan, K Wang, ... arXiv preprint arXiv:2310.03295, 2023 | 4 | 2023 |
Graph-based similarity of neural network representations Z Chen, Y Lu, J Hu, W Yang, Q Xuan, Z Wang, X Yang arXiv preprint arXiv:2111.11165, 2021 | 3 | 2021 |
Adversarial sample detection via channel pruning Z Chen, RX Wang, Y Lu, Q Xuan ICML workshop, 2021 | 3 | 2021 |
A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models Y Lu, Y Zhu, Y Li, D Xu, Y Lin, Q Xuan, X Yang arXiv preprint arXiv:2406.07929, 2024 | | 2024 |
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property Prediction Z Wang, T Jiang, Y Lu, X Bao, S Yu, B Wei, Q Xuan arXiv preprint arXiv:2405.15544, 2024 | | 2024 |
Side Channel Based Substitute Adversarial Attack on Deep Learning Models Z Chen, J Hu, Y Lu, D Zhang, Y Xiang, Q Xuan | | 2024 |
Exploring the Impact of Dataset Bias on Dataset Distillation Y Lu, J Gu, X Chen, S Vahidian, Q Xuan CVPR workshop, 7656-7663, 2024 | | 2024 |
How Does Contrastive Learning Organize Images? Y Zhang, Y Lu, Q Xuan WACV workshop, 497-506, 2024 | | 2024 |
RK-core: An Established Methodology for Exploring the Hierarchical Structure within Datasets Y Lu, Y Huang, J Nie, Z Chen, Q Xuan 2024 IEEE International Conference on Acoustics, Speech and Signal Processing, 2023 | | 2023 |