• Corpus ID: 235593001

Sparsistent Model Discovery

@article{Tod2021SparsistentMD,
  title={Sparsistent Model Discovery},
  author={Georges Tod and Gert-Jan Both and Remy Kusters},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.11936}
}
Discovering the partial differential equations underlying a spatio-temporal datasets from very limited observations is of paramount interest in many scientific fields. However, it remains an open question to know when model discovery algorithms based on sparse regression can actually recover the underlying physical processes. We trace back the poor of performance of Lasso based model discovery algorithms to its potential variable selection inconsistency: meaning that even if the true model is… 

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