Research papers

  1. Y. Jiang. Wasserstein multivariate autoregressive models and its application in graph learning from distributional time series. arXiv preprint arXiv: 2207.05442. 2022.

  2. Y. Jiang, J. Bigot & S. Maabout. Online graph topology learning from matrix-valued time series. arXiv preprint arXiv:2107.08020. 2021.

  3. Y. Jiang, J. Bigot & S. Maabout. Sensor selection on graphs via data-driven node sub-sampling in network time series. arXiv preprint arXiv:2004.11815. 2020.

  4. Y. Jiang, J. Bigot, E. Provenzi. Commutativity of spatiochromatic covariance matrices in natural image statistics. Mathematics in Engineering. 2020, 2(2): 313-339. The work is conducted in the context of the Master 2 internship at Institut de Mathématiques de Bordeaux.

PhD Thesis

Statistical analysis of spatio-temporal and multi-dimensional data from a network of sensors. (Defense slides)

Reports

Y. Jiang, G Vergara-Hermosilla. Machine learning-based modelling and forecasting of covid-19 under the temporally varying public intervention in the Chilean context. Hal: hal-03680677. 2022.

F. Coppini, Y. Jiang, S. Tabti. Predictive models on 1D signals in a small-data environment. Hal: hal-03211100. 2020. This report is the result of work during the Semaine d’'Etudes Math'ematiques et Entreprises, where 4 teams of PhD students were dedicated to solve the problems proposed by the partner companies.