ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2301.13476
  4. Cited By
An investigation of challenges encountered when specifying training data
  and runtime monitors for safety critical ML applications

An investigation of challenges encountered when specifying training data and runtime monitors for safety critical ML applications

31 January 2023
Hans-Martin Heyn
E. Knauss
Iswarya Malleswaran
Shruthi Dinakaran
ArXivPDFHTML

Papers citing "An investigation of challenges encountered when specifying training data and runtime monitors for safety critical ML applications"

5 / 5 papers shown
Title
RE-centric Recommendations for the Development of Trustworthy(er)
  Autonomous Systems
RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems
Krishna Ronanki
Beatriz Cabrero-Daniel
Jennifer Horkoff
C. Berger
11
7
0
29 May 2023
VEDLIoT -- Next generation accelerated AIoT systems and applications
VEDLIoT -- Next generation accelerated AIoT systems and applications
Kevin Mika
R. Griessl
N. Kucza
F. Porrmann
M. Kaiser
...
Mario Porrmann
Hans-Martin Heyn
E. Knauss
Yufei Mao
Franz Meierhofer
14
2
0
09 May 2023
A Survey on Bias in Visual Datasets
A Survey on Bias in Visual Datasets
Simone Fabbrizzi
Symeon Papadopoulos
Eirini Ntoutsi
Y. Kompatsiaris
119
119
0
16 Jul 2021
MLDemon: Deployment Monitoring for Machine Learning Systems
MLDemon: Deployment Monitoring for Machine Learning Systems
Antonio A. Ginart
Martin Jinye Zhang
James Y. Zou
37
18
0
28 Apr 2021
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
294
4,187
0
23 Aug 2019
1