MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. - Chuanxia Zheng; Long Tung Vuong; Jianfei Cai 001; Dinh Q. Phung (CoRR, 2022)

Vision Transformer Visualization: What Neurons Tell and How Neurons Behave? - Van-Anh Nguyen; Khanh Pham Dinh; Long Tung Vuong; Thanh-Toan Do; Quan Hung Tran; Dinh Q. Phung; Trung Le 001 (CoRR, 2022)

Vector Quantized Wasserstein Auto-Encoder. - Long Tung Vuong; Trung Le 001; He Zhao 001; Chuanxia Zheng; Mehrtash Harandi; Jianfei Cai 001; Dinh Q. Phung (ICML, 2023)

Flat Seeking Bayesian Neural Networks. - Van-Anh Nguyen; Long Tung Vuong; Hoang Phan; Thanh-Toan Do; Dinh Q. Phung; Trung Le 001 (CoRR, 2023)

Learning Directed Graphical Models with Optimal Transport. - Vy Vo; Trung Le 001; Long Tung Vuong; He Zhao 001; Edwin V. Bonilla; Dinh Q. Phung (CoRR, 2023)

Parameter Estimation in DAGs from Incomplete Data via Optimal Transport. - Vy Vo; Trung Le 001; Long Tung Vuong; He Zhao 001; Edwin V. Bonilla; Dinh Phung 001 (ICML, 2024)

Connective Viewpoints of Signal-to-Noise Diffusion Models. - Khanh Doan; Long Tung Vuong; Tuan Nguyen 004; Anh Tuan Bui; Quyen Tran; Thanh-Toan Do; Dinh Phung 001; Trung Le 001 (CoRR, 2024)

Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation. - Anh Bui; Long Tung Vuong; Khanh Doan; Trung Le 001; Paul Montague; Tamas Abraham; Dinh Q. Phung (CoRR, 2024)

Task-Driven Discrete Representation Learning. - Long Tung Vuong (AISTATS, 2025)

Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them. - Anh Tuan Bui; Thuy-Trang Vu; Long Tung Vuong; Trung Le 001; Paul Montague; Tamas Abraham; Junae Kim; Dinh Phung 001 (ICLR, 2025)

Why Domain Generalization Fail? A View of Necessity and Sufficiency. - Long Tung Vuong; Vy Vo; Hien Dang 004; Van-Anh Nguyen; Thanh-Toan Do; Mehrtash Harandi; Trung Le 001; Dinh Q. Phung (CoRR, 2025)