Zhang, Jiaru

8 publications

TMLR 2026 Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding Jiaru Zhang, Juanwu Lu, Xiaoyu Wu, Ziran Wang, Ruqi Zhang

AISTATS 2025 Learning Identifiable Structures Helps Avoid Bias in DNN-Based Supervised Causal Learning Jiaru Zhang, Rui Ding, Qiang Fu, Huang Bojun, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang

ICML 2025 Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models Xiaoyu Wu, Jiaru Zhang, Steven Wu

ICCV 2025 Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-Wise Gradient Alignment Qingqian Yang, Peishen Yan, Xiaoyu Wu, Jiaru Zhang, Tao Song, Yang Hua, Hao Wang, Liangliang Wang, Haibing Guan

CVPR 2024 CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion Xiaoyu Wu, Yang Hua, Chumeng Liang, Jiaru Zhang, Hao Wang, Tao Song, Haibing Guan

ICML 2023 Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan

AAAI 2022 Improving Bayesian Neural Networks by Adversarial Sampling Jiaru Zhang, Yang Hua, Tao Song, Hao Wang, Zhengui Xue, Ruhui Ma, Haibing Guan

CVPR 2021 Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization Jiaru Zhang, Yang Hua, Zhengui Xue, Tao Song, Chengyu Zheng, Ruhui Ma, Haibing Guan