Publications

2024

1. ICML

   Outlier-robust Kalman Filtering through Generalised Bayes

   Gerardo Durán-Martı́n, Matias Altamirano, Alexander Y Briol, and 5 more authors

   In International Conference on Machine Learning, 2024

   arXiv Bib Code

   @inproceedings{duran2024outlier,
     title = {Outlier-robust Kalman Filtering through Generalised Bayes},
     author = {Dur{\'a}n-Mart{\'\i}n, Gerardo and Altamirano, Matias and Briol, Shestopaloff, Alexander Y and S\'anchez-Betancourt, Leandro and Knoblauch, Jeremias and Jones, Matt and Fran{\c{c}}ois-Xavier and Murphy, Kevin},
     booktitle = {International Conference on Machine Learning},
     year = {2024},
   }

2. ICML

   Robust and Conjugate Gaussian Process Regression

   Matias Altamirano, François-Xavier Briol, and Jeremias Knoblauch

   In International Conference on Machine Learning, 2024

   arXiv Bib Code

   @inproceedings{altamirano2024robustGP,
     title = {Robust and Conjugate Gaussian Process Regression},
     author = {Altamirano, Matias and Briol, Fran{\c{c}}ois-Xavier and Knoblauch, Jeremias},
     booktitle = {International Conference on Machine Learning},
     year = {2024},
   }

2023

1. ICML

   Robust and Scalable Bayesian Online Changepoint Detection

   Matias Altamirano, François-Xavier Briol, and Jeremias Knoblauch

   In International Conference on Machine Learning, 2023

   arXiv Bib Code

   @inproceedings{altamirano2023robust,
     title = {Robust and Scalable {B}ayesian Online Changepoint Detection},
     author = {Altamirano, Matias and Briol, Fran{\c{c}}ois-Xavier and Knoblauch, Jeremias},
     booktitle = {International Conference on Machine Learning},
     year = {2023},
   }

2022

1. AISTATS

   Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures

   Matias Altamirano, and Felipe Tobar

   In International Conference on Artificial Intelligence and Statistics, 2022

   Bib

   @inproceedings{altamirano2022nonstationary,
     title = { Nonstationary multi-output {G}aussian processes via harmonizable spectral mixtures },
     author = {Altamirano, Matias and Tobar, Felipe},
     booktitle = {International Conference on Artificial Intelligence and Statistics},
     pages = {3204--3218},
     year = {2022},
   }

2021

1. Neurocomputing

   Unsupervised characterization of lessons according to temporal patterns of teacher talk via topic modeling

   Matias Altamirano, Pablo Uribe, Danner Schlotterbeck, and 4 more authors

   Neurocomputing, 2021

   Bib

   @article{altamirano2021unsupervised,
     title = {Unsupervised characterization of lessons according to temporal patterns of teacher talk via topic modeling},
     journal = {Neurocomputing},
     year = {2021},
     issn = {0925-2312},
     author = {Altamirano, Matias and Uribe, Pablo and Schlotterbeck, Danner and Jiménez, Abelino and Araya, Roberto and {van der Molen Moris}, Johan and Caballero, Daniela},
   }

2020

1. MIS4TEL

   Lessons Clustering Using Topics Inferred by Unsupervised Modeling from Textbooks

   Matias Altamirano, Abelino Jiménez, and Roberto Araya

   In International Conference in Methodologies and intelligent Systems for Techhnology Enhanced Learning, 2020

   Bib

   @inproceedings{altamirano2020lessons,
     title = {Lessons Clustering Using Topics Inferred by Unsupervised Modeling from Textbooks},
     author = {Altamirano, Matias and Jim{\'e}nez, Abelino and Araya, Roberto},
     booktitle = {International Conference in Methodologies and intelligent Systems for Techhnology Enhanced Learning},
     pages = {85--94},
     year = {2020},
     organization = {Springer},
   }