CITATION.cff

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cff-version: 1.2.0
title: MOTrainer
message: >-
  Distributed Measurement Operator Trainer for Data
  Assimilation Applications
type: software
authors:
  - given-names: Ou
    family-names: Ku
    email: o.ku@esciencecenter.nl
    affiliation: Netherlands eScience Center
    orcid: 'https://orcid.org/0000-0002-5373-5209'
  - given-names: Fakhereh (Sarah)
    family-names: Alidoost
    orcid: 'https://orcid.org/0000-0001-8407-6472'
    affiliation: Netherlands eScience Center
  - given-names: Xu
    family-names: Shan
    orcid: 'https://orcid.org/0000-0002-0569-4326'
    affiliation: Delft University of Technology
  - given-names: Pranav
    family-names: Chandramouli
    orcid: 'https://orcid.org/0000-0002-7896-2969'
    affiliation: Netherlands eScience Center
  - given-names: Georgievska
    family-names: Sonja
    orcid: 'https://orcid.org/0000-0002-8094-4532'
    affiliation: Netherlands eScience Center
  - given-names: Meiert
    family-names: Grootes
    orcid: 'https://orcid.org/0000-0002-5733-4795'
    affiliation: Netherlands eScience Center
  - given-names: Susan
    family-names: Steele-Dunne
    orcid: 'https://orcid.org/0000-0002-8644-3077'
    affiliation: Delft University of Technology
identifiers:
  - type: doi
    value: 10.5281/zenodo.7540442
repository-code: 'https://github.com/VegeWaterDynamics/motrainer'
url: 'https://vegewaterdynamics.github.io/motrainer/'
abstract: >-
  Measurement Operator Trainer is a Python package training
  measurement operators (MO) for data assimilations
  purposes. It is specifically designed for the applications
  where one needs to split large spatio-temporal data into
  independent partitions, and then train separate ML models
  for each partition.
keywords:
  - Measurement Operator
  - Data Assimilation
  - Machine Learning
  - Kalman Filter
license: Apache-2.0