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Lydia Gauerhof
ORCID
Publication Activity (10 Years)
Years Active: 2016-2022
Publications (10 Years): 14
Top Topics
Machine Learning
Impact Analysis
Anomaly Detection
Evidential Reasoning
Top Venues
SAFECOMP Workshops
SAFECOMP
ISSRE Workshops
PRDC
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Publications
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Carmen Cârlan
,
Lydia Gauerhof
,
Barbara Gallina
,
Simon Burton
Automating Safety Argument Change Impact Analysis for Machine Learning Components.
PRDC
(2022)
Lydia Gauerhof
,
Roman Gansch
,
Christian Heinzemann
,
Matthias Woehrle
,
Andreas Heyl
On the Necessity of Explicit Artifact Links in Safety Assurance Cases for Machine Learning.
ISSRE Workshops
(2021)
Stephanie Abrecht
,
Lydia Gauerhof
,
Christoph Gladisch
,
Konrad Groh
,
Christian Heinzemann
,
Matthias Woehrle
Testing Deep Learning-based Visual Perception for Automated Driving.
ACM Trans. Cyber Phys. Syst.
5 (4) (2021)
Andrey Morozov
,
Emil Valiev
,
Michael Beyer
,
Kai Ding
,
Lydia Gauerhof
,
Christoph Schorn
Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers.
AISafety@IJCAI
(2020)
Christoph Schorn
,
Lydia Gauerhof
FACER: A Universal Framework for Detecting Anomalous Operation of Deep Neural Networks.
ITSC
(2020)
Gesina Schwalbe
,
Bernhard Knie
,
Timo Sämann
,
Timo Dobberphul
,
Lydia Gauerhof
,
Shervin Raafatnia
,
Vittorio Rocco
Structuring the Safety Argumentation for Deep Neural Network Based Perception in Automotive Applications.
SAFECOMP Workshops
(2020)
Lydia Gauerhof
,
Nianlong Gu
Reverse Variational Autoencoder for Visual Attribute Manipulation and Anomaly Detection.
WACV
(2020)
Lydia Gauerhof
,
Yuki Hagiwara
,
Christoph Schorn
,
Mario Trapp
Considering Reliability of Deep Learning Function to Boost Data Suitability and Anomaly Detection.
ISSRE Workshops
(2020)
Michael Beyer
,
Andrey Morozov
,
Emil Valiev
,
Christoph Schorn
,
Lydia Gauerhof
,
Kai Ding
,
Klaus Janschek
Fault Injectors for TensorFlow: Evaluation of the Impact of Random Hardware Faults on Deep CNNs.
CoRR
(2020)
Lydia Gauerhof
,
Richard Hawkins
,
Chiara Picardi
,
Colin Paterson
,
Yuki Hagiwara
,
Ibrahim Habli
Assuring the Safety of Machine Learning for Pedestrian Detection at Crossings.
SAFECOMP
(2020)
Simon Burton
,
Lydia Gauerhof
,
Bibhuti Bhusan Sethy
,
Ibrahim Habli
,
Richard Hawkins
Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions.
SAFECOMP Workshops
(2019)
Lydia Gauerhof
,
Peter Munk
,
Simon Burton
Structuring Validation Targets of a Machine Learning Function Applied to Automated Driving.
SAFECOMP
(2018)
Simon Burton
,
Lydia Gauerhof
,
Christian Heinzemann
Making the Case for Safety of Machine Learning in Highly Automated Driving.
SAFECOMP Workshops
(2017)
Lydia Gauerhof
,
Anito Bilic
,
Christian Knies
,
Frank Diermeyer
Integration of a dynamic model in a driving simulator to meet requirements of various levels of automatization.
Intelligent Vehicles Symposium
(2016)