Cuong Nguyen

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Gustavo CarneiroProfessor of AI and Machine Learning, University of SurreyVerified email at surrey.ac.uk
Thanh-Toan DoSenior Lecturer, Monash UniversityVerified email at monash.edu
Arpit GargAustralian Institute for Machine Learning (AIML), School of Computer Science, University of AdelaideVerified email at adelaide.edu.au
Rafael FélixThe University of AdelaideVerified email at adelaide.edu.au
Stephen Warren-SmithFuture Industries Institute, University of South AustraliaVerified email at unisa.edu.au
Heike Ebendorff-HeidepriemUniversity of AdelaideVerified email at adelaide.edu.au
Linh Viet NguyenResearch Fellow, University of South AustraliaVerified email at unisa.edu.au
Jacinto C. NascimentoInstitute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior TécnicoVerified email at isr.ist.utl.pt
Damith C. RanasingheThe University of Adelaide, University of CambridgeVerified email at cs.adelaide.edu.au
Said Al-SarawiSchool of Electrical and Electronic Engineering, The University of AdelaideVerified email at eleceng.adelaide.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Trung LeFaculty of Information Technology, Monash University, AustraliaVerified email at monash.edu
Gabriel MaicasThe University of AdelaideVerified email at adelaide.edu.au
Farbod T. MotlaghUniversity of Adelaide, Google IncVerified email at adelaide.edu.au
Youssef DawoudPhD Candidate at Friedrich-Alexander University Erlangen, NurembergVerified email at fau.de
Vasileios BelagiannisProfessor, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Cuong Pham (Phạm Văn Cường)Posts & Telecommunications Institute of Technology and VinAI ResearchVerified email at ptit.edu.vn
Dung Hoang AnhUniversity of AdelaideVerified email at hdu.edu.vn
Cuong PhamMonash UniversityVerified email at monash.edu
Zheng ZhangUniversity of SurreyVerified email at surrey.ac.uk

Cuong Nguyen

Research fellow, University of Surrey

Verified email at surrey.ac.uk - Homepage

Machine Learning Bayesian Inference Probabilistic Programming


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Uncertainty in model-agnostic meta-learning using variational inference C Nguyen, TT Do, G Carneiro The IEEE Winter Conference on Applications of Computer Vision, 3090-3100, 2020	70	2020
Sensing in the presence of strong noise by deep learning of dynamic multimode fiber interference LV Nguyen, CC Nguyen, G Carneiro, H Ebendorff-Heidepriem, ... Photonics Research 9 (4), B109-B118, 2021	65	2021
Instance-Dependent Noisy Label Learning via Graphical Modelling A Garg, C Nguyen, R Felix, TT Do, G Carneiro Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023	37	2023
PAC-Bayes Meta-learning with Implicit Task-specific Posteriors CC Nguyen, TT Do, G Carneiro IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022	14*	2022
Analytical modeling and optimization of electret-based microgenerators under sinusoidal excitations CC Nguyen, DC Ranasinghe, SF Al-Sarawi Microsystem Technologies 23 (12), 5855-5865, 2017	11	2017
Unsupervised Task Design to Meta-Train Medical Image Classifiers G Maicas, C Nguyen, F Motlagh, JC Nascimento, G Carneiro 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1339-1342, 2020	9	2020
Probabilistic task modelling for meta-learning CC Nguyen, TT Do, G Carneiro Uncertainty in Artificial Intelligence, 781-791, 2021	8	2021
Similarity of Classification Tasks C Nguyen, TT Do, G Carneiro NeurIPS workshop on meta-learning, 2021	8	2021
Task Weighting in Meta-learning with Trajectory Optimisation CC Nguyen, TT Do, G Carneiro Transactions on Machine Learning Research, 2023	4	2023
Instance-dependent Noisy-label Learning with Graphical Model Based Noise-rate Estimation A Garg, C Nguyen, R Felix, TT Do, G Carneiro European Conference on Computer Vision, 372-389, 2025	2*	2025
Model and feature diversity for bayesian neural networks in mutual learning C Pham, CC Nguyen, T Le, D Phung, G Carneiro, TT Do Thirty-seventh Conference on Neural Information Processing Systems, 2023	2	2023
PASS: Peer-Agreement based Sample Selection for training with Noisy Labels A Garg, C Nguyen, R Felix, TT Do, G Carneiro arXiv preprint arXiv:2303.10802, 2023	2	2023
Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning DA Hoang, C Nguyen, B Vasileios, G Carneiro arXiv preprint arXiv:2208.08132, 2022	2	2022
Electret-based microgenerators under sinusoidal excitations: an analytical modeling CC Nguyen, DC Ranasinghe, SF Al-Sarawi Smart Structures and Systems 21 (3), 335-347, 2018	2	2018
Smart task design for meta learning medical image analysis systems: Unsupervised, weakly-supervised, and cross-domain design of meta learning tasks CC Nguyen, Y Dawoud, TT Do, JC Nascimento, V Belagiannis, ... Meta-Learning with Medical Imaging and Health Informatics Applications, 185-209, 2023	1	2023
Coverage-Constrained Human-AI Cooperation with Multiple Experts Z Zhang, C Nguyen, K Wells, TT Do, G Carneiro arXiv preprint arXiv:2411.11976, 2024		2024
MetaAug: Meta-Data Augmentation for Post-Training Quantization C Pham, HA Dung, CC Nguyen, T Le, D Phung, G Carneiro, TT Do arXiv preprint arXiv:2407.14726, 2024		2024
Towards the Identifiability in Noisy Label Learning: A Multinomial Mixture Approach C Nguyen, TT Do, G Carneiro arXiv preprint arXiv:2301.01405, 2023		2023
Harnessing meta-learning via probabilistic modelling and trajectory optimisation CC Nguyen University of Adelaide, 2021		2021
Analytical modeling of electret-based microgenerators under sinusoidal vibrations C Nguyen University of Adelaide, 2017		2017

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