Network In Network M Lin, Q Chen, S Yan International Conference on Learning Representations, 2013 | 9485 | 2013 |
Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ... | 2792 | 2015 |
On the spectral bias of neural networks N Rahaman, A Baratin, D Arpit, F Draxler, M Lin, F Hamprecht, Y Bengio, ... International conference on machine learning, 5301-5310, 2019 | 1236 | 2019 |
Gradient based sample selection for online continual learning R Aljundi, M Lin, B Goujaud, Y Bengio Advances in neural information processing systems 32, 2019 | 817 | 2019 |
HCP: A Flexible CNN Framework for Multi-label Image Classification Y Wei, W Xia, M Lin, J Huang, B Ni, J Dong, Y Zhao, S Yan IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 | 672 | 2015 |
Online continual learning with maximal interfered retrieval R Aljundi, E Belilovsky, T Tuytelaars, L Charlin, M Caccia, M Lin, ... Advances in neural information processing systems 32, 2019 | 531 | 2019 |
NUS-PRO: A New Visual Tracking Challenge A Li, M Lin, Y Wu, MH Yang, S Yan IEEE transactions on pattern analysis and machine intelligence 38, 335--349, 2016 | 213 | 2016 |
Online fast adaptation and knowledge accumulation (osaka): a new approach to continual learning M Caccia, P Rodriguez, O Ostapenko, F Normandin, M Lin, ... Advances in Neural Information Processing Systems 33, 16532-16545, 2020 | 142* | 2020 |
Better diffusion models further improve adversarial training Z Wang, T Pang, C Du, M Lin, W Liu, S Yan International Conference on Machine Learning, 36246-36263, 2023 | 132 | 2023 |
Causal attention for interpretable and generalizable graph classification Y Sui, X Wang, J Wu, M Lin, X He, TS Chua Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 112 | 2022 |
Robustness and accuracy could be reconcilable by (proper) definition T Pang, M Lin, X Yang, J Zhu, S Yan International Conference on Machine Learning, 17258-17277, 2022 | 107 | 2022 |
Correntropy induced l2 graph for robust subspace clustering C Lu, J Tang, M Lin, L Lin, S Yan, Z Lin Proceedings of the IEEE International Conference on Computer Vision, 1801--1808, 2013 | 102 | 2013 |
On evaluating adversarial robustness of large vision-language models Y Zhao, T Pang, C Du, X Yang, C Li, NMM Cheung, M Lin Advances in Neural Information Processing Systems 36, 2024 | 81 | 2024 |
Causal representation learning for out-of-distribution recommendation W Wang, X Lin, F Feng, X He, M Lin, TS Chua Proceedings of the ACM Web Conference 2022, 3562-3571, 2022 | 78 | 2022 |
Lorahub: Efficient cross-task generalization via dynamic lora composition C Huang, Q Liu, BY Lin, T Pang, C Du, M Lin arXiv preprint arXiv:2307.13269, 2023 | 68 | 2023 |
A recipe for watermarking diffusion models Y Zhao, T Pang, C Du, X Yang, NM Cheung, M Lin arXiv preprint arXiv:2303.10137, 2023 | 65 | 2023 |
Programming a Pavlovian-like conditioning circuit in Escherichia coli H Zhang, M Lin, H Shi, W Ji, L Huang, X Zhang, S Shen, R Gao, S Wu, ... Nature communications 5 (1), 3102, 2014 | 50 | 2014 |
How should pre-trained language models be fine-tuned towards adversarial robustness? X Dong, AT Luu, M Lin, S Yan, H Zhang Advances in Neural Information Processing Systems 34, 4356-4369, 2021 | 48 | 2021 |
Envpool: A highly parallel reinforcement learning environment execution engine J Weng, M Lin, S Huang, B Liu, D Makoviichuk, V Makoviychuk, Z Liu, ... Advances in Neural Information Processing Systems 35, 22409-22421, 2022 | 40 | 2022 |
Softmax gan M Lin arXiv preprint arXiv:1704.06191, 2017 | 28 | 2017 |