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M. Pacheco

3 papers hereh-index 252.2k citations160 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • eess.IV1
  • stat.ML1
same name
  • M. Pacheco — 23 papers, h 24
  • M. Pacheco — 3 papers, h 3
  • M. Pacheco — 3 papers, h 4
  • M. Pacheco — 3 papers, h 1
  • M. Pacheco — 3 papers, h 5
  • M. Pacheco — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedTowards a Robust Parameterization for Conditioning Facies Models Using Deep Variational Autoencoders and Ensemble Smoother

178 citations · 244 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2020★ 3 cited

A free web service for fast COVID-19 classification of chest X-Ray images

Jose David Bermudez Castro, Ricardo Rei, Jose E. Ruiz +6

The coronavirus outbreak became a major concern for society worldwide. Technological innovation and ingenuity are essential to fight COVID-19 pandemic and bring us one step closer…

cs.LG2020★ 63 cited

Recent Developments Combining Ensemble Smoother and Deep Generative Networks for Facies History Matching

Smith W. A. Canchumuni, Jose D. B. Castro, Júlia Potratz +2

Ensemble smoothers are among the most successful and efficient techniques currently available for history matching. However, because these methods rely on Gaussian assumptions, the…

stat.ML2018★ 178 cited

Towards a Robust Parameterization for Conditioning Facies Models Using Deep Variational Autoencoders and Ensemble Smoother

Smith W. A. Canchumuni, Alexandre A. Emerick, Marco Aurélio C. Pacheco

The literature about history matching is vast and despite the impressive number of methods proposed and the significant progresses reported in the last decade, conditioning reservo…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.