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Giovanni Sansavini

3 papers here

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

author position
  • middle author1
  • last author2

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

fields
  • cs.LG1
  • math.OC1
  • physics.soc-ph1
ORCID 0000-0002-8801-9667

identity via Semantic Scholar / OpenAlex

most citedUncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines

3 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

math.OC2024★ 1 cited

Funplex: A Modified Simplex Algorithm to Efficiently Explore Near-Optimal Spaces

Christoph S. Funke, Linda Brodnicke, Francesco Lombardi +1

Modeling to generate alternatives (MGA) is an increasingly popular method in energy system optimization. MGA explores the near-optimal space, namely, system alternatives whose cost…

cs.LG2023★ 3 cited

Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines

Laya Das, Blazhe Gjorgiev, Giovanni Sansavini

Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data…

physics.soc-ph2023

Resilient Design in Nuclear Energy: Critical Lessons from a Cross-Disciplinary Review of the Fukushima Dai-ichi Nuclear Accident

Ali Ayoub, Haruko Wainwright, Giovanni Sansavini +2

Nuclear energy has been gaining momentum recently as one of the solutions to tackle climate change. However, significant environmental and health-risk concerns remain associated wi…

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