Zheng Zhao

Orcid: 0000-0002-0368-786X

Affiliations:
  • Uppsala University, Sweden
  • Aalto University, Finland (PhD 2021)


According to our database1, Zheng Zhao authored at least 23 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Probabilistic Estimation of Instantaneous Frequencies of Chirp Signals.
IEEE Trans. Signal Process., 2023

Multidimensional projection filters via automatic differentiation and sparse-grid integration.
Signal Process., 2023

On Feynman-Kac training of partial Bayesian neural networks.
CoRR, 2023

Controlling Vision-Language Models for Universal Image Restoration.
CoRR, 2023

Image Restoration with Mean-Reverting Stochastic Differential Equations.
Proceedings of the International Conference on Machine Learning, 2023

NTIRE 2023 Challenge on Stereo Image Super-Resolution: Methods and Results.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NTIRE 2023 Image Shadow Removal Challenge Report.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023



2022
Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review.
IEEE Trans. Intell. Transp. Syst., 2022

Non-Linear Gaussian Smoothing With Taylor Moment Expansion.
IEEE Signal Process. Lett., 2022

Fast optimize-and-sample method for differentiable Galerkin approximations of multi-layered Gaussian process priors.
Proceedings of the 25th International Conference on Information Fusion, 2022

Temporal Gaussian Process Regression in Logarithmic Time.
Proceedings of the 25th International Conference on Information Fusion, 2022

2021
Taylor Moment Expansion for Continuous-Discrete Gaussian Filtering.
IEEE Trans. Autom. Control., 2021

Deep state-space Gaussian processes.
Stat. Comput., 2021

Gaussian Process Regression in Logarithmic Time.
CoRR, 2021

2020
Kalman-based Spectro-Temporal ECG Analysis using Deep Convolutional Networks for Atrial Fibrillation Detection.
J. Signal Process. Syst., 2020

Parameter Estimation in Non-Linear State-Space Models by Automatic Differentiation of Non-Linear Kalman Filters.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network.
CoRR, 2019

Regularized State Estimation And Parameter Learning Via Augmented Lagrangian Kalman Smoother Method.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

2018
Spectro-Temporal ECG Analysis for atrial fibrillation Detection.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018


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