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researcher

Maximilian Poretschkin

2 papers here

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

author position
  • middle author1
  • last author1

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

fields
  • cs.AI1
  • cs.LG1
same name
  • Maximilian Poretschkin — 1 paper, h 7

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 citedA Survey on Uncertainty Toolkits for Deep Learning

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

collaborators

2 papers

cs.AI2024★ 1 cited

Developing trustworthy AI applications with foundation models

Michael Mock, Sebastian Schmidt, Felix Müller +6

The trustworthiness of AI applications has been the subject of recent research and is also addressed in the EU's recently adopted AI Regulation. The currently emerging foundation m…

cs.LG2022★ 1 cited

A Survey on Uncertainty Toolkits for Deep Learning

Maximilian Pintz, Joachim Sicking, Maximilian Poretschkin +1

The success of deep learning (DL) fostered the creation of unifying frameworks such as tensorflow or pytorch as much as it was driven by their creation in return. Having common bui…

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