Full interpretable machine learning in 2D with inline coordinates. - Boris Kovalerchuk; Hoang Phan (IV, 2021)

Stochastic Multiple Target Sampling Gradient Descent. - Hoang Phan; Ngoc Tran; Trung Le 001; Toan Tran 003; Nhat Ho; Dinh Phung 001 (NeurIPS, 2022)

Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation. - Hoang Phan; Anh Phan Tuan; Son Nguyen; Ngo Van Linh 001; Khoat Than (PAKDD (1), 2022)

Global-Local Regularization Via Distributional Robustness. - Hoang Phan; Trung Le 001; Trung Phung; Tuan-Anh Bui; Nhat Ho; Dinh Q. Phung (CoRR, 2022)

Improving Multi-task Learning via Seeking Task-based Flat Regions. - Hoang Phan; Lam Tran; Ngoc N. Tran; Nhat Ho; Dinh Q. Phung; Trung Le 001 (CoRR, 2022)

Continual Learning with Optimal Transport based Mixture Model. - Quyen Tran; Hoang Phan; Khoat Than; Dinh Q. Phung; Trung Le 001 (CoRR, 2022)

Global-Local Regularization Via Distributional Robustness. - Hoang Phan; Trung Le 001; Trung Phung; Anh Tuan Bui; Nhat Ho; Dinh Q. Phung (AISTATS, 2023)

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

Sharpness & Shift-Aware Self-Supervised Learning. - Ngoc N. Tran; Son Duong; Hoang Phan; Tung Pham 001; Dinh Q. Phung; Trung Le 001 (CoRR, 2023)

Full High-Dimensional Intelligible Learning In 2-D Lossless Visualization Space. - Boris Kovalerchuk; Hoang Phan (CoRR, 2023)

Robust Contrastive Learning With Theory Guarantee. - Ngoc N. Tran; Lam Tran; Hoang Phan; Anh Tuan Bui; Tung Pham 001; Toan Tran 003; Dinh Q. Phung; Trung Le 001 (CoRR, 2023)

Controllable Prompt Tuning For Balancing Group Distributional Robustness. - Hoang Phan; Andrew Gordon Wilson; Qi Lei (ICML, 2024)

Enhancing Domain Adaptation through Prompt Gradient Alignment. - Hoang Phan; Lam Tran; Quyen Tran; Trung Le 001 (CoRR, 2024)

Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning. - Yijun Dong; Hoang Phan; Xiang Pan 001; Qi Lei (CoRR, 2024)

DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation. - Hao Phung; Quan Dao; Trung Tuan Dao; Hoang Phan; Dimitris N. Metaxas; Anh Tuan Tran 001 (CoRR, 2024)

Unveiling Concept Attribution in Diffusion Models. - Quang H. Nguyen; Hoang Phan; Khoa D. Doan (CoRR, 2024)

Personalized Large Vision-Language Models. - Chau Pham; Hoang Phan; David S. Doermann; Yunjie Tian (CoRR, 2024)

PLVM: A tuning-free approach for Personalized Large Vision-Language Model. - Chau Pham; Hoang Phan; David S. Doermann; Yunjie Tian (CVPR Workshops, 2025)

Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation. - Tung-Long Vuong; Hoang Phan; Vy Vo; Anh Bui; Thanh-Toan Do; Trung Le 001; Dinh Phung 001 (CVPR, 2025)