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researcher

Mikel Sanz

7 papers hereh-index 488 citations8 works total

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

author position
  • middle author3
  • last author4

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • quant-ph3
  • physics.flu-dyn1
same name
  • Mikel Sanz — 8 papers, h 3
  • Mikel Sanz — 7 papers, h 2
  • Mikel Sanz — 5 papers, h 1
  • Mikel Sanz — 4 papers, h 2
  • Mikel Sanz — 4 papers, h 1
  • Mikel Sanz — 1 paper, h 1

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

activity
20232026
most citedResidual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants

31 citations · 65 across the 7 of their papers we have counts for

collaborators
Showing 2024Show all

3 papers · 1 filter

quant-ph2024★ 9 cited

Quantum Carleman linearisation efficiency in nonlinear fluid dynamics

Javier Gonzalez-Conde, Dylan Lewis, Sachin S. Bharadwaj +1

Computational fluid dynamics (CFD) is a specialised branch of fluid mechanics that utilises numerical methods and algorithms to solve and analyze fluid-flow problems. One promising…

cs.LG2024★ 31 cited

Residual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants

Ibai Ramirez, Joel Pino, David Pardo +5

Transformers are crucial for reliable and efficient power system operations, particularly in supporting the integration of renewable energy. Effective monitoring of transformer hea…

quant-ph2024★ 3 cited

Existence of unbiased resilient estimators in discrete quantum systems

Javier Navarro, Ricard Ravell Rodríguez, Mikel Sanz

The Cramér-Rao bound serves as a crucial lower limit for the mean squared error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prio…

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