Tamara Fernández

Publications

Current and published work in statistical inference, kernel methods, and survival analysis.

Work in progress

  1. A Multiple Kernel Testing Procedure for Non-Proportional Hazards in Factorial Designs.
    With Marc Ditzhaus and Nicolás Rivera. Preprint.
  2. Kernel Tests for Martingales.
    With Merle Munko and Nicolás Rivera.
  3. A Kernel Test for the Proportional Hazards Assumption.
    With Merle Munko and Nicolás Rivera.
  4. Clustering Point Processes through Distributional Representations.
    With Nicolás Rivera, Tomás Sanhueza and Wenkai Xu.
  5. A Kernelized Approach to Multiple Contrast Testing in General Multivariate Factorial Designs.
    With Nicolás Rivera. Submitted to Journal of Multivariate Analysis.

Published

  1. Composite Goodness-of-fit Tests with Kernels.
    With Oscar Key, Arthur Gretton and François-Xavier Briol.
    Journal of Machine Learning Research, 26(51):1–60, 2025. Paper.
  2. A General Framework for the Analysis of Kernel-based Tests.
    With Nicolás Rivera.
    Journal of Machine Learning Research, 25(95):1–40, 2024. Paper.
  3. A Kernel Log-Rank Test of Independence for Right-Censored Data.
    With Arthur Gretton, David Rindt and Dino Sejdinovic.
    Journal of the American Statistical Association, 118(542):925–936, 2023. Paper, arXiv.
  4. A Reproducing Kernel Hilbert Space Log-Rank Test for the Two-Sample Problem.
    With Nicolás Rivera.
    Scandinavian Journal of Statistics, 48(4):1384–1432, 2021. Paper.
  5. Kaplan–Meier V- and U-statistics.
    With Nicolás Rivera.
    Electronic Journal of Statistics, 14:1872–1916, 2020. Paper.
  6. A Kernel Test for Quasi-Independence.
    With Wenkai Xu, Marc Ditzhaus and Arthur Gretton.
    Advances in Neural Information Processing Systems (NeurIPS), 2020. Paper.
  7. Kernelized Stein Discrepancy Tests of Goodness-of-Fit for Time-to-Event Data.
    With Nicolás Rivera, Wenkai Xu and Arthur Gretton.
    International Conference on Machine Learning (ICML), 2020. Paper.
  8. A Maximum-Mean-Discrepancy Goodness-of-Fit Test for Censored Data.
    With Arthur Gretton.
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. Paper.
  9. Gaussian Processes for Survival Analysis.
    With Nicolás Rivera and Yee Whye Teh.
    Advances in Neural Information Processing Systems (NeurIPS), 2016. Paper.
  10. Posterior Consistency for a Non-Parametric Survival Model under a Gaussian Process Prior.
    With Yee Whye Teh. Technical report. arXiv.