Robust Bayesian Neural Networks by Spectral Expectation Bound Regularization. - Jiaru Zhang; Yang Hua 001; Zhengui Xue; Tao Song 003; Chengyu Zheng; Ruhui Ma; Haibing Guan (CVPR, 2021)

Hierarchical Satellite System Graph for Approximate Nearest Neighbor Search on Big Data. - Jiaru Zhang; Ruhui Ma; Tao Song 003; Yang Hua 001; Zhengui Xue; Chenyang Guan; Haibing Guan (Trans. Data Sci., 2021)

Improving Bayesian Neural Networks by Adversarial Sampling. - Jiaru Zhang; Yang Hua 001; Tao Song 003; Hao Wang 022; Zhengui Xue; Ruhui Ma; Haibing Guan (AAAI, 2022)

Information Bound and Its Applications in Bayesian Neural Networks. - Jiaru Zhang; Yang Hua 001; Tao Song 003; Hao Wang 022; Zhengui Xue; Ruhui Ma; Haibing Guan (ECAI, 2023)

Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples. - Chumeng Liang; Xiaoyu Wu; Yang Hua 001; Jiaru Zhang; Yiming Xue; Tao Song 003; Zhengui Xue; Ruhui Ma; Haibing Guan (ICML, 2023)

CGI-DM: Digital Copyright Authentication for Diffusion Models via Contrasting Gradient Inversion. - Xiaoyu Wu; Yang Hua 001; Chumeng Liang; Jiaru Zhang; Hao Wang 022; Tao Song 003; Haibing Guan (CVPR, 2024)

Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior. - Pingchuan Ma 004; Rui Ding 001; Qiang Fu 015; Jiaru Zhang; Shuai Wang 011; Shi Han; Dongmei Zhang 001 (KDD, 2024)

Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks. - Xiaoyu Wu; Jiaru Zhang; Yang Hua 001; Bohan Lyu 001; Hao Wang 022; Tao Song 003; Haibing Guan (CoRR, 2024)

Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version). - Pingchuan Ma 004; Rui Ding 001; Qiang Fu 015; Jiaru Zhang; Shuai Wang 011; Shi Han; Dongmei Zhang 001 (CoRR, 2024)

Revealing the Unseen: Guiding Personalized Diffusion Models to Expose Training Data. - Xiaoyu Wu; Jiaru Zhang; Steven Wu 001 (CoRR, 2024)

Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning. - Jiaru Zhang; Rui Ding 001; Qiang Fu 015; Bojun Huang; Zizhen Deng; Yang Hua 001; Haibing Guan; Shi Han; Dongmei Zhang 001 (AISTATS, 2025)

THOR: A Generic Energy Estimation Approach for On-Device Training. - Jiaru Zhang; Zesong Wang; Hao Wang 022; Tao Song 003; Huai-an Su; Rui Chen 026; Yang Hua 001; Xiangwei Zhou; Ruhui Ma; Miao Pan; Haibing Guan (CoRR, 2025)

Inference Acceleration of Autoregressive Normalizing Flows by Selective Jacobi Decoding. - Jiaru Zhang; Juanwu Lu; Ziran Wang; Ruqi Zhang (CoRR, 2025)