◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

A. Schütze

3 papers here

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

author position
  • middle author3

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

fields
  • cs.LG1
  • eess.SP1
  • eess.SY1

identity via Semantic Scholar / OpenAlex

most citedComparing AutoML and Deep Learning Methods for Condition Monitoring using Realistic Validation Scenarios

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

collaborators

3 papers

eess.SY2024

Experimentally implemented dynamic optogenetic optimization of ATPase expression using knowledge-based and Gaussian-process-supported models

Sebastián Espinel-Ríos, Gerrich Behrendt, Jasmin Bauer +6

Optogenetic modulation of adenosine triphosphatase (ATPase) expression represents a novel approach to maximize bioprocess efficiency by leveraging enforced adenosine triphosphate (…

cs.LG2023★ 2 cited

Comparing AutoML and Deep Learning Methods for Condition Monitoring using Realistic Validation Scenarios

Payman Goodarzi, Andreas Schütze, Tizian Schneider

This study extensively compares conventional machine learning methods and deep learning for condition monitoring tasks using an AutoML toolbox. The experiments reveal consistent hi…

eess.SP2023

Deep convolutional neural networks for cyclic sensor data

Payman Goodarzi, Yannick Robin, Andreas Schütze +1

Predictive maintenance plays a critical role in ensuring the uninterrupted operation of industrial systems and mitigating the potential risks associated with system failures. This…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.