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researcher

M. Bubel

3 papers here

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

author position
  • first author3

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

fields
  • cs.CE2
  • stat.ME1

identity via Semantic Scholar / OpenAlex

most citedCubature-based uncertainty estimation for nonlinear regression models

1 citations · 1 across the 3 of their papers we have counts for

collaborators
Showing cs.CEShow all

2 papers · 1 filter

cs.CE2025

A Machine Learning-Fueled Modelfluid for Flowsheet Optimization

Martin Bubel, Tobias Seidel, Michael Bortz

Process optimization in chemical engineering may be hindered by the limited availability of reliable thermodynamic data for fluid mixtures. Remarkable progress is being made in pre…

cs.CE2025

Reusable Surrogate Models for Distillation Columns

Martin Bubel, Tobias Seidel, Michael Bortz

Surrogate modeling is a powerful methodology in chemical process engineering, frequently employed to accelerate optimization tasks where traditional flowsheet simulators are comput…

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