Large-scale distance metric learning for k-nearest neighbors regression. - Bac Nguyen; Carlos Morell 001; Bernard De Baets (Neurocomputing, 2016)

Distance metric learning: a two-phase approach. - Bac Nguyen; Carlos Morell 001; Bernard De Baets (ESANN, 2017)

Supervised distance metric learning through maximization of the Jeffrey divergence. - Bac Nguyen; Carlos Morell 001; Bernard De Baets (Pattern Recognit., 2017)

Distance metric learning with the Universum. - Bac Nguyen; Carlos Morell 001; Bernard De Baets (Pattern Recognit. Lett., 2017)

Distance metric learning for ordinal classification based on triplet constraints. - Bac Nguyen; Carlos Morell 001; Bernard De Baets (Knowl. Based Syst., 2018)

An approach to supervised distance metric learning based on difference of convex functions programming. - Bac Nguyen; Bernard De Baets (Pattern Recognit., 2018)

An efficient method for clustered multi-metric learning. - Bac Nguyen; Francesc J. Ferri; Carlos Morell 001; Bernard De Baets (Inf. Sci., 2019)

Kernel Distance Metric Learning Using Pairwise Constraints for Person Re-Identification. - Bac Nguyen; Bernard De Baets (IEEE Trans. Image Process., 2019)

Kernel-Based Distance Metric Learning for Supervised k-Means Clustering. - Bac Nguyen; Bernard De Baets (IEEE Trans. Neural Networks Learn. Syst., 2019)

Improved deep embedding learning based on stochastic symmetric triplet loss and local sampling. - Bac Nguyen; Bernard De Baets (Neurocomputing, 2020)

Scalable Large-Margin Distance Metric Learning Using Stochastic Gradient Descent. - Bac Nguyen; Carlos Morell 001; Bernard De Baets (IEEE Trans. Cybern., 2020)

Otolith identification using a deep hierarchical classification model. - Michiel Stock; Bac Nguyen; Wouter Courtens; Hilbran Verstraete; Eric W. M. Stienen; Bernard De Baets (Comput. Electron. Agric., 2021)

A Simple Approach for Zero-Shot Learning based on Triplet Distribution Embeddings. - Vivek Chalumuri; Bac Nguyen (CoRR, 2021)

NVC-Net: End-To-End Adversarial Voice Conversion. - Bac Nguyen; Fabien Cardinaux (ICASSP, 2022)

Neural Predictor for Black-Box Adversarial Attacks on Speech Recognition. - Marie Biolková; Bac Nguyen (CoRR, 2022)

Resource orchestration and digitalisation at a public hospital in Vietnam. - Duy Dang-Pham; Karlheinz Kautz; Mathews Nkhoma; Mai Do Thi Hoang; Phuong Do; Bac Nguyen (ACIS, 2023)

Autotts: End-to-End Text-to-Speech Synthesis Through Differentiable Duration Modeling. - Bac Nguyen; Fabien Cardinaux; Stefan Uhlich (ICASSP, 2023)

Improving Self-Supervised Learning for Audio Representations by Feature Diversity and Decorrelation. - Bac Nguyen; Stefan Uhlich; Fabien Cardinaux (ICASSP, 2023)

Towards Robust FastSpeech 2 by Modelling Residual Multimodality. - Fabian Kögel; Bac Nguyen; Fabien Cardinaux (INTERSPEECH, 2023)

SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning. - Bac Nguyen; Stefan Uhlich; Fabien Cardinaux; Lukas Mauch; Marzieh Edraki; Aaron C. Courville (ECCV (69), 2024)

SPARO: Selective Attention for Robust and Compositional Transformer Encodings for Vision. - Ankit Vani; Bac Nguyen; Samuel Lavoie; Ranjay Krishna; Aaron C. Courville (ECCV (66), 2024)

Skill: Similarity-Aware Knowledge Distillation for Speech Self-Supervised Learning. - Luca Zampierin; Ghouthi Boukli Hacene; Bac Nguyen; Mirco Ravanelli (ICASSP Workshops, 2024)

G2D2: Gradient-guided Discrete Diffusion for image inverse problem solving. - Naoki Murata; Chieh-Hsin Lai; Yuhta Takida; Toshimitsu Uesaka; Bac Nguyen; Stefano Ermon; Yuki Mitsufuji (CoRR, 2024)

Mitigating Embedding Collapse in Diffusion Models for Categorical Data. - Bac Nguyen; Chieh-Hsin Lai; Yuhta Takida; Naoki Murata; Toshimitsu Uesaka; Stefano Ermon; Yuki Mitsufuji (CoRR, 2024)

G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving. - Naoki Murata; Chieh-Hsin Lai; Yuhta Takida; Toshimitsu Uesaka; Bac Nguyen; Stefano Ermon; Yuki Mitsufuji (Trans. Mach. Learn. Res., 2025)