| A bayesian data augmentation approach for learning deep models T Tran, T Pham, G Carneiro, L Palmer, I Reid Advances in neural information processing systems 30, 2017 | 287 | 2017 |
| Bayesian Generative Active Deep Learning T Tran, TT Do, I Reid, G Carneiro International Conference on Machine Learning (ICML), 2019 | 162 | 2019 |
| Exploiting domain-specific features to enhance domain generalization MH Bui, T Tran, A Tran, D Phung Advances in Neural Information Processing Systems 34, 21189-21201, 2021 | 123 | 2021 |
| Domain invariant representation learning with domain density transformations AT Nguyen, T Tran, Y Gal, AG Baydin Advances in Neural Information Processing Systems 34, 5264-5275, 2021 | 71 | 2021 |
| A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning TT Do, T Tran, I Reid, V Kumar, T Hoang, G Carneiro The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 71 | 2019 |
| KL guided domain adaptation AT Nguyen, T Tran, Y Gal, PHS Torr, AG Baydin International Conference on Learning Representations (ICLR), 2021 | 39 | 2021 |
| A novel genetic algorithm approach for simultaneous feature and classifier selection in multi classifier system TT Nguyen, AWC Liew, MT Tran, XC Pham, MP Nguyen 2014 IEEE Congress on Evolutionary Computation (CEC), 1698-1705, 2014 | 33 | 2014 |
| Combining multi classifiers based on a genetic algorithm–a gaussian mixture model framework TT Nguyen, AWC Liew, MT Tran, MP Nguyen Intelligent Computing Methodologies: 10th International Conference, ICIC …, 2014 | 18 | 2014 |
| On learning domain-invariant representations for transfer learning with multiple sources T Phung, T Le, TL Vuong, T Tran, A Tran, H Bui, D Phung Advances in Neural Information Processing Systems 34, 27720-27733, 2021 | 16 | 2021 |
| Distributionally Robust Fair Principal Components via Geodesic Descents H Vu, T Tran, MC Yue, VA Nguyen International Conference on Learning Representations (ICLR), 2022 | 13 | 2022 |
| Fusion of classifiers based on a novel 2-stage model TT Nguyen, AWC Liew, MT Tran, TTT Nguyen, MP Nguyen Machine Learning and Cybernetics: 13th International Conference, Lanzhou …, 2014 | 9 | 2014 |
| Learning fractional white noises in neural stochastic differential equations A Tong, T Nguyen-Tang, T Tran, J Choi Advances in Neural Information Processing Systems 35, 37660-37675, 2022 | 8 | 2022 |
| Stochastic Multiple Target Sampling Gradient Descent H Phan, N Tran, T Le, T Tran, N Ho, D Phung Advances in Neural Information Processing Systems, 2022 | 6 | 2022 |
| Learning compositional sparse gaussian processes with a shrinkage prior A Tong, TM Tran, H Bui, J Choi Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9906-9914, 2021 | 3 | 2021 |
| Combining classifiers based on gaussian mixture model approach to ensemble data TT Nguyen, AWC Liew, MT Tran, MP Nguyen Machine Learning and Cybernetics: 13th International Conference, Lanzhou …, 2014 | 3 | 2014 |
| KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All Q Tran, L Tran, K Than, T Tran, D Phung, T Le arXiv preprint arXiv:2311.15414, 2023 | 1 | 2023 |
| Reducing Training Time in Cross-Silo Federated Learning using Multigraph Topology T Do, BX Nguyen, V Pham, T Tran, E Tjiputra, Q Tran, A Nguyen International Conference on Computer Vision (ICCV), 2023 | 1 | 2023 |
| Multigraph topology design for cross-silo federated learning BX Nguyen, T Do, H Nguyen, V Pham, T Tran, E Tjiputra, Q Tran, ... arXiv preprint arXiv:2207.09657, 2022 | 1 | 2022 |
| Bayesian Data Augmentation and Generative Active Learning for Robust Imbalanced Deep Learning TM Tran | 1 | 2020 |
| Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All Q Tran, TL Tran, K Than, T Tran, D Phung, T Le | 1 | |
Gustavo CarneiroProfessor of AI and Machine Learning, University of SurreyVerified email at surrey.ac.uk
