Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks. - Peizhi Niu; Chao Pan 003; Siheng Chen; Olgica Milenkovic (CoRR, 2024)

Improve Certified Training with Signal-to-Noise Ratio Loss to Decrease Neuron Variance and Increase Neuron Stability. - Tianhao Wei; Ziwei Wang 001; Peizhi Niu; Abulikemu Abuduweili; Weiye Zhao; Casidhe Hutchison; Eric M. Sample; Changliu Liu (Trans. Mach. Learn. Res., 2024)

ModelVerification.jl: A Comprehensive Toolbox for Formally Verifying Deep Neural Networks. - Tianhao Wei; Hanjiang Hu; Luca Marzari; Kai S. Yun; Peizhi Niu; Xusheng Luo; Changliu Liu (CAV (2), 2025)

DMol: A Schedule-Driven Diffusion Model for Highly Efficient and Versatile Molecule Generation. - Peizhi Niu; Yu-Hsiang Wang; Vishal Rana; Chetan Rupakheti; Abhishek Pandey; Olgica Milenkovic (CoRR, 2025)

Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness. - Rongzhe Wei; Peizhi Niu; Hans Hao-Hsun Hsu; Ruihan Wu; Haoteng Yin; Mohsen Ghassemi; Yifan Li; Vamsi K. Potluru; Eli Chien; Kamalika Chaudhuri; Olgica Milenkovic; Pan Li 005 (CoRR, 2025)

GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models. - Evelyn Ma; Duo Zhou; Peizhi Niu; Huiting Zhou; Huan Zhang 001; Olgica Milenkovic; S. Rasoul Etesami 001 (CoRR, 2025)

3DGS-IEval-15K: A Large-scale Image Quality Evaluation Database for 3D Gaussian-Splatting. - Yuke Xing; Jiarui Wang; Peizhi Niu; Wenjie Huang; Guangtao Zhai; Yiling Xu (CoRR, 2025)