Unsupervised Task Design to Meta-Train Medical Image Classifiers. - Gabriel Maicas; Cuong Nguyen 006; Farbod Motlagh; Jacinto C. Nascimento; Gustavo Carneiro 001 (ISBI, 2020)

Uncertainty in Model-Agnostic Meta-Learning using Variational Inference. - Cuong Nguyen 006; Thanh-Toan Do; Gustavo Carneiro 001 (WACV, 2020)

PAC-Bayesian Meta-learning with Implicit Prior. - Cuong Nguyen 006; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2020)

Probabilistic task modelling for meta-learning. - Cuong Cao Nguyen; Thanh-Toan Do; Gustavo Carneiro 001 (UAI, 2021)

Similarity of Classification Tasks. - Cuong Nguyen 006; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2021)

Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning. - Dung Anh Hoang; Cuong Nguyen 006; Vasileios Belagiannis; Gustavo Carneiro 001 (CoRR, 2022)

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. - Van Cuong Pham; Cuong C. Nguyen; Trung Le 001; Dinh Phung 001; Gustavo Carneiro 001; Thanh-Toan Do (NeurIPS, 2023)

Instance-Dependent Noisy Label Learning via Graphical Modelling. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (WACV, 2023)

Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach. - Cuong Nguyen 006; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2023)

PASS: Peer-Agreement based Sample Selection for training with Noisy Labels. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2023)

Noisy-label Learning with Sample Selection based on Noise Rate Estimate. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2023)

PAC-Bayes Meta-Learning With Implicit Task-Specific Posteriors. - Cuong Nguyen 006; Thanh-Toan Do; Gustavo Carneiro 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Task Weighting in Meta-learning with Trajectory Optimisation. - Cuong C. Nguyen; Thanh-Toan Do; Gustavo Carneiro 001 (Trans. Mach. Learn. Res., 2023)

Instance-Dependent Noisy-Label Learning with Graphical Model Based Noise-Rate Estimation. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (ECCV (4), 2024)

MetaAug: Meta-data Augmentation for Post-training Quantization. - Cuong Pham 007; Hoang Anh Dung; Cuong C. Nguyen; Trung Le 001; Dinh Phung 001; Gustavo Carneiro 001; Thanh-Toan Do (ECCV (27), 2024)

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning. - Cuong Pham 007; Cuong C. Nguyen; Trung Le 001; Dinh Q. Phung; Gustavo Carneiro 001; Thanh-Toan Do (CoRR, 2024)

Coverage-Constrained Human-AI Cooperation with Multiple Experts. - Zheng Zhang 046; Cuong Nguyen 006; Kevin Wells; Thanh-Toan Do; David Rosewarne; Gustavo Carneiro 001 (CoRR, 2024)

Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution. - Cuong C. Nguyen; Thanh-Toan Do; Gustavo Carneiro 001 (ICLR, 2025)

Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning. - Hoang Anh Dung; Cuong C. Nguyen; Vasileios Belagiannis; Thanh-Toan Do; Gustavo Carneiro 001 (Trans. Mach. Learn. Res., 2025)

AEON: Adaptive Estimation of Instance-Dependent In-Distribution and Out-of-Distribution Label Noise for Robust Learning. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Yuyuan Liu; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2025)