A Generalized Loss Function for Crowd Counting and Localization J Wan, Z Liu, AB Chan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 181 | 2021 |
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks Q Wu, T Yang, Z Liu, B Wu, Y Shan, AB Chan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 42 | 2023 |
Improved Fine-tuning by Better Leveraging Pre-training Data Z Liu, Y Xu, Y Xu, Q Qian, H Li, A Chan, R Jin Advances in Neural Information Processing Systems (NeurIPS), 2022 | 29* | 2022 |
Fully Nested Neural Network for Adaptive Compression and Quantization Y Cui, Z Liu, W Yao, Q Li, AB Chan, T Kuo, CJ Xue IJCAI-PRICAI 2020, 2020 | 16 | 2020 |
An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation Z Liu, Y Xu, Y Xu, Q Qian, H Li, R Jin, X Ji, AB Chan NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 14 | 2022 |
Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images CUI Yufei, Z Liu, X Liu, X Liu, C Wang, TW Kuo, CJ Xue, AB Chan International Conference on Learning Representations, 2023 | 13 | 2023 |
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations Z Liu, Y Cui, AB Chan ICML 2021 Workshop on Adversarial Machine Learning, 2020 | 13 | 2020 |
Clustering hidden Markov models with variational Bayesian hierarchical EM H Lan, Z Liu, JH Hsiao, D Yu, AB Chan IEEE Transactions on Neural Networks and Learning Systems 34 (3), 1537-1551, 2021 | 9 | 2021 |
Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions RI Masoud, Z Liu, M Ferianc, P Treleaven, M Rodrigues arXiv preprint arXiv:2309.12342, 2023 | 8 | 2023 |
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Z Liu, AB Chan BMVC 2022, 2022 | 7 | 2022 |
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression Y Cui, Z Liu, Q Li, Y Mao, AB Chan, CJ Xue Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 7 | 2021 |
Variational Nested Dropout Y Cui, Y Mao, Z Liu, Q Li, AB Chan, X Liu, TW Kuo, CJ Xue IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 5 | 2023 |
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization Z Liu, Y Xu, X Ji, AB Chan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models Z Liu, L Yu, JH Hsiao, AB Chan IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 3 | 2021 |
Parametric Manifold Learning of Gaussian Mixture Models Z Liu, L Yu, JH Hsiao, AB Chan IJCAI-2019, Proceedings of the Twenty-Eighth International Joint Conference …, 2019 | 3 | 2019 |
Retrieval-Augmented Multiple Instance Learning CUI Yufei, Z Liu, C Yixin, Y Lu, X Yu, X Liu, TW Kuo, MRD Rodrigues, ... Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023 | 1* | 2023 |
Borrowing Treasures from Neighbors: In-Context Learning for Multimodal Learning with Missing Modalities and Data Scarcity Z Zhi, Z Liu, M Elbadawi, A Daneshmend, M Orlu, A Basit, ... arXiv preprint arXiv:2403.09428, 2024 | | 2024 |
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks Z Liu, Z Zhi, I Bogunovic, C Gerner-Beuerle, M Rodrigues NeurIPS 2023 Workshop on Regulatable ML, 2023 | | 2023 |
Weight Rescaling: Effective and Robust Regularization for Deep Neural Networks with Batch Normalization Z Liu, Y Cui, J Wan, Y Mao, AB Chan arXiv preprint arXiv:2102.03497, 2021 | | 2021 |