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ORCIDZhidi Lin
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2020 – today
- 2024
[j2]Zhidi Lin
, Yiyong Sun, Feng Yin, Alexandre Hoang Thiery:
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference. IEEE Trans. Signal Process. 72: 4286-4301 (2024)- [c11]Yuanhang Zhang, Zhidi Lin, Yiyong Sun, Feng Yin, Carsten Fritsche:
Regularization-Based Efficient Continual Learning in Deep State-Space Models. FUSION 2024: 1-8 - [c10]Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis:
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models. ICASSP 2024: 12881-12885 - [c9]Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang:
Preventing Model Collapse in Gaussian Process Latent Variable Models. ICML 2024 - [i9]Yuanhang Zhang, Zhidi Lin, Yiyong Sun, Feng Yin, Carsten Fritsche:
Regularization-Based Efficient Continual Learning in Deep State-Space Models. CoRR abs/2403.10123 (2024) - [i8]Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang:
Preventing Model Collapse in Gaussian Process Latent Variable Models. CoRR abs/2404.01697 (2024) - 2023
- [c8]Zhidi Lin, Lei Cheng, Feng Yin, Lexi Xu, Shuguang Cui:
Output-Dependent Gaussian Process State-Space Model. ICASSP 2023: 1-5 - [i7]Zhidi Lin, Feng Yin:
Towards Flexibility and Interpretability of Gaussian Process State-Space Model. CoRR abs/2301.08843 (2023) - [i6]Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis:
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models. CoRR abs/2309.01074 (2023) - [i5]Richard Cornelius Suwandi, Zhidi Lin, Feng Yin:
Gaussian Processes with Linear Multiple Kernel: Spectrum Design and Distributed Learning for Multi-Dimensional Data. CoRR abs/2309.08201 (2023) - [i4]Zhidi Lin, Yiyong Sun, Feng Yin, Alexandre Hoang Thiery:
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference. CoRR abs/2312.05910 (2023) - 2022
- [c7]Richard Cornelius Suwandi, Zhidi Lin, Yiyong Sun, Zhiguo Wang, Lei Cheng, Feng Yin:
Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data. FUSION 2022: 1-8 - [c6]Xinyi Zhang, Chenxu Zhao, Yun Yang, Zhidi Lin, Juntao Wang, Feng Yin:
Adaptive Gaussian Process Spectral Kernel Learning for 5G Wireless Traffic Prediction. MLSP 2022: 1-6 - [i3]Zhidi Lin, Lei Cheng, Feng Yin, Lexi Xu, Shuguang Cui:
Output-Dependent Gaussian Process State-Space Model. CoRR abs/2212.07608 (2022) - 2021
- [c5]Wenzhong Yan, Di Jin, Zhidi Lin, Feng Yin:
Graph Neural Network for Large-Scale Network Localization. ICASSP 2021: 5250-5254 - 2020
- [j1]Zhidi Lin, Dongliang Duan, Qi Yang, Xuemin Hong, Xiang Cheng, Liuqing Yang, Shuguang Cui:
One-Class Classifier Based Fault Detection in Distribution Systems With Varying Penetration Levels of Distributed Energy Resources. IEEE Access 8: 130023-130035 (2020) - [c4]Yijue Dai, Tianjian Zhang, Zhidi Lin, Feng Yin, Sergios Theodoridis, Shuguang Cui:
An Interpretable and Sample Efficient Deep Kernel for Gaussian Process. UAI 2020: 759-768 - [i2]Feng Yin, Zhidi Lin, Yue Xu, Qinglei Kong, Deshi Li, Sergios Theodoridis, Shuguang Cui:
FedLoc: Federated Learning Framework for Cooperative Localization and Location Data Processing. CoRR abs/2003.03697 (2020) - [i1]Wenzhong Yan, Di Jin, Zhidi Lin, Feng Yin:
Graph Neural Network for Large-Scale Network Localization. CoRR abs/2010.11653 (2020)
2010 – 2019
- 2019
- [c3]Zhidi Lin, Haipeng Chen, Qi Yang, Xuemin Hong:
A Flexible Approach for Human Activity Recognition Based on Broad Learning System. ICMLC 2019: 368-373 - 2018
- [c2]Zhidi Lin, Dongliang Duan, Qi Yang, Xiang Cheng, Liuqing Yang, Shuguang Cui:
One-Class Classifier Based Fault Detection in Distribution Systems with Distributed Energy Resources. GlobalSIP 2018: 932-936 - [c1]Shuqing Lin, Feng Yin, Zhidi Lin, Yanbin Lin, Shuguang Robert Cui, Teng Li, Fengli Yu, Wei Yu, Xuemin Hong, Jianghong Shi, Zhi-Quan Tom Luo:
Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset. ICCC 2018: 68-73
Coauthor Index
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