Yuhao Liu

According to our database, Yuhao Liu authored at least 11 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Gaussian Process-Gated Hierarchical Mixtures of Experts.

Yuhao Liu, Marzieh Ajirak, Petar M. Djuric

IEEE Trans. Pattern Anal. Mach. Intell., September, 2024

Novel Architecture of Deep Feature-Based Gaussian Processes with an Ensemble of Kernels.

Yuanqing Song, Yuhao Liu, Petar M. Djuric

Proceedings of the IEEE International Conference on Acoustics, 2024

Filtering of High-Dimensional Data for Sequential Classification.

Marzieh Ajirak, Yuhao Liu, Petar M. Djuric

Proceedings of the 27th International Conference on Information Fusion, 2024

2023

Sequential Estimation of Gaussian Process-Based Deep State-Space Models.

Yuhao Liu, Marzieh Ajirak, Petar M. Djuric

IEEE Trans. Signal Process., 2023

Estimation of Time-Varying Graph Topologies from Graph Signals.

Yuhao Liu, Chen Cui, Marzieh Ajirak, Petar M. Djuric

Proceedings of the IEEE International Conference on Acoustics, 2023

Detecting Confounders in Multivariate Time Series using Strength of Causation.

Yuhao Liu, Chen Cui, Daniel Waxman, Kurt Butler, Petar M. Djuric

Proceedings of the 31st European Signal Processing Conference, 2023

2022

Tracking the Dimensions of Latent Spaces of Gaussian Process Latent Variable Models.

Yuhao Liu, Petar M. Djuric

Proceedings of the IEEE International Conference on Acoustics, 2022

Inference with Deep Gaussian Process State Space Models.

Yuhao Liu, Marzieh Ajirak, Petar M. Djuric

Proceedings of the 30th European Signal Processing Conference, 2022

Ensembles of Gaussian process latent variable models.

Marzieh Ajirak, Yuhao Liu, Petar M. Djuric

Proceedings of the 30th European Signal Processing Conference, 2022

2021

The Use of Gaussian Processes as Particles for Sequential Monte Carlo Estimation of Time-Varying Functions.

Yuhao Liu, Petar M. Djuric

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Gaussian Process State-Space Models with Time-Varying Parameters and Inducing Points.

Yuhao Liu, Petar M. Djuric

Proceedings of the 28th European Signal Processing Conference, 2020