6 citations · 11 across the 21 of their papers we have counts for
4 papers · 1 filter
Your Classifier Can Do More: Towards Balancing the Gaps in Classification, Robustness, and Generation
Kaichao Jiang, He Wang, Xiaoshuai Hao +5
Joint Energy-based Models (JEMs) are well known for their ability to unify classification and generation within a single framework. Despite their promising generative and discrimin…
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
Jingjing Hu, Dan Guo, Zhan Si +5
Molecular representation learning plays a crucial role in various downstream tasks, such as molecular property prediction and drug design. To accurately represent molecules, Graph…
Moderating the Generalization of Score-based Generative Model
Wan Jiang, He Wang, Xin Zhang +4
Score-based Generative Models (SGMs) have demonstrated remarkable generalization abilities, e.g. generating unseen, but natural data. However, the greater the generalization power,…
Unlearnable Examples Give a False Sense of Security: Piercing through Unexploitable Data with Learnable Examples
Wan Jiang, Yunfeng Diao, He Wang +3
Safeguarding data from unauthorized exploitation is vital for privacy and security, especially in recent rampant research in security breach such as adversarial/membership attacks.…