Publications by years in reversed chronological order



  1. A hierarchical model to evaluate pest treatments from prevalence and intensity data
    Armand Favrot, and David Makoswki
    Computo, 2024.


  1. Local tree methods for classification: a review and some dead ends
    Alice Cleynen, Louis Raynal, and Jean-Michel Marin
    Computo, 2023.
  2. Computing an empirical Fisher information matrix estimate in latent variable models through stochastic approximation
    Maud Delattre, and Estelle Kuhn
    Computo, 2023.
  3. Inference of Multiscale Gaussian Graphical Model
    Edmond Sanou, Christophe Ambroise, and Geneviève Robin
    Computo, 2023.
  4. Macrolitter Video Counting on Riverbanks Using State Space Models and Moving Cameras
    Mathis Chagneux, Sylvain Le Corff, Pierre Gloaguen, Charles Ollion, Océane Lepâtre, and Antoine Bruge
    Computo, 2023.
  5. A Python Package for Sampling from Copulae: clayton
    Alexis Boulin
    Computo, 2023.


  1. Trade-off between deep learning for species identification and inference about predator-prey co-occurrence: Reproducible R workflow integrating models in computer vision and ecological statistics
    Olivier Gimenez, Maelis Kervellec, Jean-Baptiste Fanjul, Anna Chaine, Lucile Marescot, Yoann Bollet, and Christophe Duchamp
    Computo, 2022.

In the pipeline

Manuscript conditionally accepted, whose editorial and scientific reproducibility is being validated

  1. Point Process Discrimination According to Repulsion
    Hamza Adrat, and Laurent Decreusefond
    Computo, 2024.
  2. Optimal projection for parametric importance sampling in high dimensions
    Maxime El Masri, Jérôme Morio, and Florian Simatos
    Computo, 2024.
  3. Peerannot: classification for crowdsourced image datasets with Python
    Tanguy Lefort, Benjamin Charlier, Alexis Joly, and Joseph Salmon
    Computo, 2024.

Under review

At the moment, 6 manuscripts are under review.

Example: a mock contribution

This page is a reworking of the original t-SNE article using the Computo template. It aims to help authors submitting to the journal by using some advanced formatting features.

  1. Visualizing Data using t-SNE: practical Computo example
    Laurens Maaten, and Geoffrey Hinton
    Computo, 2021.