Generalized Local Aggregation for Large Scale Gaussian Process Regression. - Yinghua Gao; Naiqi Li; Ning Ding 002; Yiming Li 004; Tao Dai 001; Shu-Tao Xia (IJCNN, 2020)

Stochastic Deep Gaussian Processes over Graphs. - Naiqi Li; Wenjie Li 008; Jifeng Sun; Yinghua Gao; Yong Jiang 001; Shu-Tao Xia (NeurIPS, 2020)

DAG-GAN: Causal Structure Learning with Generative Adversarial Nets. - Yinghua Gao; Li Shen 008; Shu-Tao Xia (ICASSP, 2021)

H-GPR: A Hybrid Strategy for Large-Scale Gaussian Process Regression. - Naiqi Li; Yinghua Gao; Wenjie Li 008; Yong Jiang 001; Shu-Tao Xia (ICASSP, 2021)

Backdoor Attack with Sparse and Invisible Trigger. - Yinghua Gao; Yiming Li 004; Xueluan Gong; Shu-Tao Xia; Qian Wang 002 (CoRR, 2023)

Not All Samples Are Born Equal: Towards Effective Clean-Label Backdoor Attacks. - Yinghua Gao; Yiming Li 004; Linghui Zhu; Dongxian Wu; Yong Jiang 001; Shu-Tao Xia (Pattern Recognit., 2023)

Backdoor Attack With Sparse and Invisible Trigger. - Yinghua Gao; Yiming Li 004; Xueluan Gong; Zhifeng Li 001; Shu-Tao Xia; Qian Wang 002 (IEEE Trans. Inf. Forensics Secur., 2024)

Node-Level Graph Regression With Deep Gaussian Process Models. - Naiqi Li; Wenjie Li 008; Yinghua Gao; Yiming Li 004; Jigang Bao; Ercan E. Kuruoglu; Yong Jiang 001; Shu-Tao Xia (IEEE Trans. Artif. Intell., 2024)

On the Effectiveness of Adversarial Training Against Backdoor Attacks. - Yinghua Gao; Dongxian Wu; Jingfeng Zhang; Guanhao Gan; Shu-Tao Xia; Gang Niu 001; Masashi Sugiyama (IEEE Trans. Neural Networks Learn. Syst., 2024)