One-Class Classifier Based Fault Detection in Distribution Systems with Distributed Energy Resources. - Zhidi Lin; Dongliang Duan; Qi Yang 006; Xiang Cheng 001; Liuqing Yang 001; Shuguang Cui (GlobalSIP, 2018)

Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset. - Shuqing Lin; Feng Yin; Zhidi Lin; Yanbin Lin; Shuguang Robert Cui; Teng Li; Fengli Yu; Wei Yu 001; Xuemin Hong; Jianghong Shi; Zhi-Quan Tom Luo (ICCC, 2018)

A Flexible Approach for Human Activity Recognition Based on Broad Learning System. - Zhidi Lin; Haipeng Chen; Qi Yang 006; Xuemin Hong (ICMLC, 2019)

An Interpretable and Sample Efficient Deep Kernel for Gaussian Process. - Yijue Dai; Tianjian Zhang; Zhidi Lin; Feng Yin; Sergios Theodoridis; Shuguang Cui (UAI, 2020)

One-Class Classifier Based Fault Detection in Distribution Systems With Varying Penetration Levels of Distributed Energy Resources. - Zhidi Lin; Dongliang Duan; Qi Yang 006; Xuemin Hong; Xiang Cheng 001; Liuqing Yang 001; Shuguang Cui (IEEE Access, 2020)

FedLoc: Federated Learning Framework for Cooperative Localization and Location Data Processing. - Feng Yin; Zhidi Lin; Yue Xu; Qinglei Kong; Deshi Li; Sergios Theodoridis; Shuguang Cui (CoRR, 2020)

Graph Neural Network for Large-Scale Network Localization. - Wenzhong Yan; Di Jin 002; Zhidi Lin; Feng Yin (ICASSP, 2021)

Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data. - Richard Cornelius Suwandi; Zhidi Lin; Yiyong Sun; Zhiguo Wang 005; Lei Cheng 003; Feng Yin (FUSION, 2022)

Adaptive Gaussian Process Spectral Kernel Learning for 5G Wireless Traffic Prediction. - Xinyi Zhang; Chenxu Zhao; Yun Yang; Zhidi Lin; Juntao Wang; Feng Yin (MLSP, 2022)

Output-Dependent Gaussian Process State-Space Model. - Zhidi Lin; Lei Cheng 003; Feng Yin; Lexi Xu; Shuguang Cui (ICASSP, 2023)

Towards Flexibility and Interpretability of Gaussian Process State-Space Model. - Zhidi Lin; Feng Yin (CoRR, 2023)

Gaussian Processes with Linear Multiple Kernel: Spectrum Design and Distributed Learning for Multi-Dimensional Data. - Richard Cornelius Suwandi; Zhidi Lin; Feng Yin (CoRR, 2023)

Regularization-Based Efficient Continual Learning in Deep State-Space Models. - Yuanhang Zhang; Zhidi Lin; Yiyong Sun; Feng Yin; Carsten Fritsche (FUSION, 2024)

Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models. - Zhidi Lin; Juan Maroñas; Ying Li; Feng Yin; Sergios Theodoridis (ICASSP, 2024)

Preventing Model Collapse in Gaussian Process Latent Variable Models. - Ying Li; Zhidi Lin; Feng Yin; Michael Minyi Zhang (ICML, 2024)

Scalable Random Feature Latent Variable Models. - Ying Li; Zhidi Lin; Yuhao Liu 002; Michael Minyi Zhang; Pablo M. Olmos; Petar M. Djuric (CoRR, 2024)

Hybrid Data-Driven SSM for Interpretable and Label-Free mmWave Channel Prediction. - Yiyong Sun; Jiajun He 001; Zhidi Lin; Wenqiang Pu; Feng Yin; Hing Cheung So (CoRR, 2024)

Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference. - Zhidi Lin; Yiyong Sun; Feng Yin; Alexandre Hoang Thiery (IEEE Trans. Signal Process., 2024)

Multi-View Oriented GPLVM: Expressiveness and Efficiency. - Zi Yang; Ying Li; Zhidi Lin; Michael Minyi Zhang; Pablo M. Olmos (CoRR, 2025)

Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems. - Zhidi Lin; Ying Li; Feng Yin; Juan Maroñas; Alexandre H. Thiéry (CoRR, 2025)