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Yuhao Liu

Publications

Please see the list of publications on Google Scholar as well.

 

Journals

  1. Ying Li, Zhidi Lin, Yuhao Liu, Michael Minyi Zhang, Pablo M. Olmos, and Petar M. Djurić. "Scalable Random Feature Latent Variable Models." IEEE Transactions on Pattern Analysis and Machine Intelligence (2025).
  2. Yuhao Liu, Ajirak Marzieh, and Petar M. Djurić. "Gaussian process-gated hierarchical mixtures of experts." IEEE Transactions on Pattern Analysis and Machine Intelligence (2024).
  3. Yuhao Liu, Ajirak Marzieh, and Petar M. Djurić. "Sequential Estimation of Gaussian Process-based Deep State-Space Models." IEEE Transactions on Signal Processing (2023).
  4. Sima Mofakham, Yuhao Liu, Asher Hensley, Jordan R. Saadon, Theresa Gammel, Megan E. Cosgrove, Joseph Adachi, et al. "Injury to thalamocortical projections following traumatic brain injury results in attractor dynamics for cortical networks." Progress in Neurobiology (2022): 102215.
  5. Yuhao Liu, Petar M. Djurić, Young Shin Kim, Svetlozar T. Rachev, and James Glimm. "Systemic risk modeling with Lévy copulas." Journal of Risk and Financial Management 14, no. 6 (2021): 251.

Conferences

  1. Yuanqing Song, Yuhao Liu, and Petar M. Djurić. "Novel Deep Gaussian Process Structures with Flexible Depths." In ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5. IEEE, 2025.
  2. Marzieh Ajirak, Yuhao Liu, and Petar M. Djurić. "Filtering of High-Dimensional Data for Sequential Classification." In 2024 27th International Conference on Information Fusion (FUSION), pp. 1-7. IEEE, 2024.
  3. Yuanqing Song, Yuhao Liu, and Petar M. Djurić. "Novel Architecture of Deep Feature-Based Gaussian Processes with an Ensemble of Kernels." In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6750-6754. IEEE, 2024.
  4. Yuhao Liu, Chen Cui, Daniel Waxman, Kurt Butler, and Petar M. Djurić. "Detecting confounders in multivariate time series using strength of causation." In 2023 31st European Signal Processing Conference (EUSIPCO), pp. 1400-1404. IEEE, 2023.
  5. Yuhao Liu, Chen Cui, Marzieh Ajirak, and Petar M. Djurić. "Estimation of Time-Varying Graph Topologies from Graph Signals." In 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1-5. IEEE, 2023.
  6. Yuhao Liu, and Petar M. Djurić. "Tracking the Dimensions of Latent Spaces of Gaussian Process Latent Variable Models." In 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4193-4197. IEEE, 2022
  7. Yuhao Liu, Ajirak Marzieh and Petar M. Djurić. "Inference with Deep Gaussian Process State Space Models." In 2022 30th European Signal Processing Conference (EUSIPCO), pp. 792-796. IEEE, 2022.
  8. Ajirak Marzieh, Yuhao Liu, and Petar M. Djurić. "Ensembles of Gaussian Process Latent Variable Models." In 2022 30th European Signal Processing Conference (EUSIPCO), pp. 1467-1471. IEEE, 2022.
  9. Yuhao Liu, and Petar M. Djurić. "The Use of Gaussian Processes as Particles for Sequential Monte Carlo Estimation of Time-Varying Functions." In 2021 29th European Signal Processing Conference (EUSIPCO), pp. 1975-1979. IEEE, 2021.
  10. Yuhao Liu, and Petar M. Djurić. "Gaussian process state-space models with time-varying parameters and inducing points." In 2020 28th European Signal Processing Conference (EUSIPCO), pp. 1462-1466. IEEE, 2021.

Book Chapters

  1. Weilin Su, He Ding, and Yuhao Liu. "Role of Supervisor as Coach and Developer." In The Oxford Handbook of Lifelong Learning, Second Edition.

Others

  1. Yuhao Liu. "Bayesian Deep Learning With Random Feature-Based Gaussian Processes" Doctoral dissertation, State University of New York at Stony Brook.
  2. Yuhao Liu, Robert D. Brook, Xuefeng Liu, and James B. Byrd. "Abstract P300: Countries’ geographic latitude and their populations’ cholesterol and blood pressure." Hypertension 72, no. Suppl_1 (2018): AP300-AP300.
  3. Petar M Djuric, Chen Cui, Yuhao Liu, Marzieh Ajirak, Paolo Banelli. "Gaussian Process-Based Learning of Dynamical Graphs." SIAM Conference on Mathematics of Data Science (MDS22), oral presentation, San Diego, California,  September 26, 2022.