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researcher

E. Lejeune

2 papers here

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

author position
  • first author1
  • last author1

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • q-bio.TO1

identity via Semantic Scholar / OpenAlex

most citedPredicting Mechanically Driven Full-Field Quantities of Interest with Deep Learning-Based Metamodels

2 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 2 cited

Predicting Mechanically Driven Full-Field Quantities of Interest with Deep Learning-Based Metamodels

S. Mohammadzadeh, E. Lejeune

Using simulation to predict the mechanical behavior of heterogeneous materials has applications ranging from topology optimization to multi-scale structural analysis. However, full…

q-bio.TO2020★ 1 cited

Exploring the potential of transfer learning for metamodels of heterogeneous material deformation

Emma Lejeune, Bill Zhao

From the nano-scale to the macro-scale, biological tissue is spatially heterogeneous. Even when tissue behavior is well understood, the exact subject specific spatial distribution…

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