Tuan-Anh Bui

2024

1. 

   Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation

   Tuan-Anh Bui, Vuong Long, Khanh Doan, and 4 more authors

   NeurIPS 2024, 2024

   Bib PDF Code Slides

   @article{bui2024adversarial,
     title = {Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation},
     author = {Bui, Tuan-Anh and Long, Vuong and Doan, Khanh and Le, Trung and Montague, Paul and Abraham, Tamas and Phung, Dinh},
     journal = {NeurIPS 2024},
     year = {2024},
     url = {https://tuananhbui89.github.io/projects/adversarial-preservation},
   }

2. 

   Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts

   Tuan-Anh Bui*, Khanh Doan*, Trung Le, and 3 more authors

   Preprint, 2024

   Bib PDF Code Slides

   @article{bui2024removing,
     title = {Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts},
     author = {Bui${*}$, Tuan-Anh and Doan${*}$, Khanh and Le, Trung and Montague, Paul and Abraham, Tamas and Phung, Dinh},
     journal = {Preprint},
     year = {2024},
     url = {https://arxiv.org/abs/2403.12326},
   }

3. 

   Diversity-Aware Agnostic Ensemble of Sharpness Minimizers

   Tuan-Anh Bui*, Vy Vo*, Tung Pham, and 2 more authors

   Preprint, 2024

   Bib PDF Code

   @article{bui2024diversity,
     title = {Diversity-Aware Agnostic Ensemble of Sharpness Minimizers},
     author = {Bui${*}$, Tuan-Anh and Vo${*}$, Vy and Pham, Tung and Phung, Dinh and Le, Trung},
     journal = {Preprint},
     year = {2024},
     url = {https://arxiv.org/abs/2403.13204},
   }

4. 

   Optimal transport model distributional robustness

   Van-Anh Nguyen, Trung Le, Tuan-Anh Bui, and 2 more authors

   Advances in Neural Information Processing Systems, 2024

   Bib PDF Code

   @article{nguyen2024optimal,
     title = {Optimal transport model distributional robustness},
     author = {Nguyen, Van-Anh and Le, Trung and Bui, Tuan-Anh and Do, Thanh-Toan and Phung, Dinh},
     journal = {Advances in Neural Information Processing Systems},
     volume = {36},
     year = {2024},
     url = {https://proceedings.neurips.cc/paper_files/paper/2023/hash/4b91825aec2ed35150f1d3e8fb195556-Abstract-Conference.html},
   }

2023

1. 

   Generating Adversarial Examples with Task Oriented Multi-Objective Optimization

   Tuan-Anh Bui, Trung Le, He Zhao, and 3 more authors

   Transactions on Machine Learning Research, 2023

   Bib PDF Code

   @article{bui2023generating,
     title = {Generating Adversarial Examples with Task Oriented Multi-Objective Optimization},
     author = {Bui, Tuan-Anh and Le, Trung and Zhao, He and Tran, Quan and Montague, Paul and Phung, Dinh},
     journal = {Transactions on Machine Learning Research},
     issn = {2835-8856},
     year = {2023},
     url = {https://openreview.net/forum?id=2f81Q622ww},
   }

2022

1. 

   A Unified Wasserstein Distributional Robustness Framework for Adversarial Training

   Tuan-Anh Bui, Trung Le, Quan Tran, and 2 more authors

   In International Conference on Learning Representations, 2022

   Bib PDF Code

   @inproceedings{bui2021unified,
     title = {A Unified Wasserstein Distributional Robustness Framework for Adversarial Training},
     author = {Bui, Tuan-Anh and Le, Trung and Tran, Quan and Zhao, He and Phung, Dinh},
     booktitle = {International Conference on Learning Representations},
     year = {2022},
   }

2021

1. 

   Understanding and achieving efficient robustness with adversarial supervised contrastive learning

   Tuan-Anh Bui, Trung Le, He Zhao, and 3 more authors

   arXiv preprint arXiv:2101.10027, 2021

   Bib PDF Code

   @article{bui2021understanding,
     title = {Understanding and achieving efficient robustness with adversarial supervised contrastive learning},
     author = {Bui, Tuan-Anh and Le, Trung and Zhao, He and Montague, Paul and Camtepe, Seyit and Phung, Dinh},
     journal = {arXiv preprint arXiv:2101.10027},
     year = {2021},
   }

2020

1. 

   Improving adversarial robustness by enforcing local and global compactness

   Tuan-Anh Bui, Trung Le, He Zhao, and 4 more authors

   In European Conference on Computer Vision, 2020

   Bib PDF Code Poster Slides

   @inproceedings{bui2020improving,
     title = {Improving adversarial robustness by enforcing local and global compactness},
     author = {Bui, Tuan-Anh and Le, Trung and Zhao, He and Montague, Paul and deVel, Olivier and Abraham, Tamas and Phung, Dinh},
     booktitle = {European Conference on Computer Vision},
     pages = {209--223},
     year = {2020},
     organization = {Springer},
   }

2019

1. 

   Improving GAN with neighbors embedding and gradient matching

   Ngoc-Trung Tran*, Tuan-Anh Bui*, and Ngai-Man Cheung

   In Proceedings of the AAAI conference on artificial intelligence, 2019

   Bib PDF Code

   @inproceedings{tran2019improving,
     title = {Improving GAN with neighbors embedding and gradient matching},
     author = {Tran${*}$, Ngoc-Trung and Bui${*}$, Tuan-Anh and Cheung, Ngai-Man},
     booktitle = {Proceedings of the AAAI conference on artificial intelligence},
     volume = {33},
     number = {01},
     pages = {5191--5198},
     year = {2019},
   }

2018

1. 

   Dist-gan: An improved gan using distance constraints

   Ngoc-Trung Tran, Tuan-Anh Bui, and Ngai-Man Cheung

   In Proceedings of the European conference on computer vision (ECCV), 2018

   Bib PDF Code

   @inproceedings{tran2018dist,
     title = {Dist-gan: An improved gan using distance constraints},
     author = {Tran, Ngoc-Trung and Bui, Tuan-Anh and Cheung, Ngai-Man},
     booktitle = {Proceedings of the European conference on computer vision (ECCV)},
     pages = {370--385},
     year = {2018},
   }