Abraham, Tamas

7 publications

ICLR 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, Paul Montague, Tamas Abraham, Junae Kim, Dinh Phung

ICLRW 2025 Hiding and Recovering Knowledge in Text-to-Image Diffusion Models via Learnable Prompts Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Phung

NeurIPS 2024 Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation Anh Bui, Long Vuong, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Phung

AAAI 2023 Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness Bao Gia Doan, Shuiqiao Yang, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Seyit Camtepe, Salil S. Kanhere, Ehsan Abbasnejad, Damith C. Ranasinghe

IJCAI 2021 Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein

AAAI 2021 Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness Tuan-Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Dinh Phung

ECCV 2020 Improving Adversarial Robustness by Enforcing Local and Global Compactness Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier deVel, Tamas Abraham, Dinh Phung