Tabish Badar, Simo Särkkä, Zheng Zhao, and Arto Visala. Rao–Blackwellized particle filter using noise adaptive Kalman filter for fully mixing state-space models. IEEE Transactions on Aerospace and Electronic Systems, 60(5):6972–6982, 2024.

Muhammad Emzir, Zheng Zhao, Lahouari Cheded, and Simo Särkkä. Gaussian-based parametric bijections for automatic projection filters. IEEE Transactions on Automatic Control, 69(5):3449–3456, 2024.

Zheng Zhao, Simo Särkkä, Jens Sjölund, and Thomas B. Schön. Probabilistic estimation of instantaneous frequencies of chirp signals. IEEE Transactions on Signal Processing, 71:461–476, 2023.

Muhammad Emzir, Zheng Zhao, and Simo Särkkä. Multidimensional projection filters via automatic differentiation and sparse-grid integration. Signal Processing, 204:108832, 2023.

Zheng Zhao and Simo Särkkä. Non-linear Gaussian smoothing with Taylor moment expansion. IEEE Signal Processing Letters, 29:80–84, 2022.

Zheng Zhao, Muhammad Emzir, and Simo Särkkä. Deep state-space Gaussian processes. Statistics and Computing, 31(6):75, 2021.

Zheng Zhao, Toni Karvonen, Roland Hostettler, and Simo Särkkä. Taylor moment expansion for continuous-discrete Gaussian filtering. IEEE Transactions on Automatic Control, 66(9):4460–4467, 2021.

Sarang Thombre, Zheng Zhao, Henrik Ramm-Schmidt, José M. Vallet García, Tuomo Malkamäki, Sergey Nikolskiy, Toni Hammarberg, Hiski Nuortie, M. Zahidul H. Bhuiyan, Simo Särkkä, and Ville V. Lehtola. Sensors and AI techniques for situational awareness in autonomous ships: a review. IEEE Transactions on Intelligent Transportation Systems, 23(1):64–83, 2022.

Zheng Zhao, Simo Särkkä, and Ali Bahrami Rad. Kalman-based spectro-temporal ECG analysis using deep convolutional networks for atrial fibrillation detection. Journal of Signal Processing Systems, 92(7):621–636, 2020.

Zheng Zhao and Naigong Yu. An improved quantum particle swarm optimisation and its application on hand kinematics tracking. International Journal of Intelligent Engineering Informatics, 2016.

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B. Schön. Photo-realistic image restoration in the wild with controlled vision-language models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.

Zheng Zhao, Sebastian Mair, Thomas B. Schön, and Jens Sjölund. On Feynman–Kac training of partial Bayesian neural networks. In Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B. Schön. Controlling vision-language models for universal image restoration. In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024.

Jennifer Rosina Andersson, Oleg Kochukhov, Zheng Zhao, and Jens Sjölund. Bayesian uncertainty quantification in high-dimensional stellar magnetic field models. In International Conference on Machine Learning (ICML) Workshop on Machine Learning for Astrophysics, 2023.

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B. Schön. Image restoration with mean-reverting stochastic differential equations. In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023.

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B. Schön. Refusion: enabling large-size realistic image restoration with latent-space diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023.

Muhammad Fuady Emzir, Niki A. Loppi, Zheng Zhao, Syeda S. Hassan, and Simo Särkkä. Fast optimize-and-sample method for differentiable Galerkin approximations of multi-layered Gaussian process priors. In Proceedings of the 25th IEEE International Conference on Information Fusion (FUSION), 2022.

Adrien Corenflos, Zheng Zhao, and Simo Särkkä. Temporal Gaussian process regression in logarithmic time. In Proceedings of the 25th IEEE International Conference on Information Fusion (FUSION), 2022.

Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä. State-space Gaussian process for drift estimation in stochastic differential equations. In Proceedings of the 45th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.

Ajinkya Gorad, Zheng Zhao, and Simo Särkkä. Parameter estimation in non-Linear state-space models by automatic differentiation of non-Linear Kalman filters. In Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2020.

Rui Gao, Filip Tronarp, Zheng Zhao, and Simo Särkkä. Regularized state estimation and parameter learning via augmented Lagrangian Kalman smoother. In Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2019.

Zheng Zhao and Simo Särkkä. Spectro-temporal ECG analysis for atrial fibrillation detection. In Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2018.

Zheng Zhao, Ziwei Luo, Jens Sjölund, and Thomas B. Schön. Conditional sampling within generative diffusion models. arxiv:2409.09650, 2024.

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B. Schön. Taming diffusion models for image restoration: a review. arxiv:2409.10353, 2024.

Adrien Corenflos*, Zheng Zhao*, Simo Särkkä, Jens Sjölund, and Thomas B. Schön. Conditioning diffusion models by explicit forward-backward bridging. arxiv:2405.13794, 2024.

Zheng Zhao and Juha Sarmavuori. Stochastic filtering with moment representation. arxiv:2303.13895, 2023.

Zheng Zhao, Rui Gao, and Simo Särkkä. Hierarchical non-stationary temporal Gaussian processes with L1-regularization. arxiv:2105.09695, 2021.

Ali Bahrami Rad, Morteza Zabihi, Zheng Zhao, Moncef Gabbouj, Aggelos K. Katsaggelos, and Simo Särkkä. Automated polysomnography analysis for detection of non-apneic and non-hypopneic arousals using feature engineering and a bidirectional LSTM network. arxiv:1909.02971, 2019.

Jennifer Rosina Andersson, Oleg Kochukhov, Zheng Zhao, and Jens Sjölund. Simulation-based inference in stellar magnetic field models. 14th International Conference on Monte Carlo Methods and Applications, 2023.

Zheng Zhao. State-space deep Gaussian processes with applications. PhD Thesis, Aalto University, 2021.