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Kai Ding 0001
Person information
- affiliation (PhD 2021): TU Dresden, Germany
Other persons with the same name
- Kai Ding — disambiguation page
- Kai Ding 0002
— University of California, Irvine, Department of Mechanical and Aerospace Engineering, USA
- Kai Ding 0003
— Johns Hopkins University, Baltimore, MD, USA (and 2 more)
- Kai Ding 0004
— Chang'an University, Institute of Smart Manufacturing Systems, Xi'an, China
- Kai Ding 0005
— Dongguan University of Technology, Dongguan, China
- Kai Ding 0006
— Jia Xing University, Jiaxing, China
- Kai Ding 0007
— The Sixth Academy of China Aerospace Science & Industry Corporation, China
- Kai Ding 0008
— Beijing Institute of Technology, Beijing Engineering Research Center of Massive Language Information Processing and Cloud Computing Application, Beijing, China
- Kai Ding 0009 — IntSig Information Co., Shanghai, China
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2020 – today
- 2021
- [b1]Kai Ding:
Zuverlässigkeitsorientierter Entwurf und Analyse von Steuerungssystemen auf Modellebene unter zufälligen Hardwarefehlern: Dependability-oriented Design and Analysis of Control Systems at the Model Level under Random Hardware Faults. TU Dresden, Germany, 2021 - 2020
- [c9]Andrey Morozov, Emil Valiev, Michael Beyer, Kai Ding, Lydia Gauerhof, Christoph Schorn:
Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers. AISafety@IJCAI 2020 - [i2]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 abs/2012.07037 (2020)
2010 – 2019
- 2019
- [c8]Kai Ding, Sheng Ding, Andrey Morozov, Tagir Fabarisov
, Klaus Janschek:
On-Line Error Detection and Mitigation for Time-Series Data of Cyber-Physical Systems using Deep Learning Based Methods. EDCC 2019: 7-14 - [c7]Michael Beyer
, Andrey Morozov, Kai Ding, Sheng Ding, Klaus Janschek:
Quantification of the Impact of Random Hardware Faults on Safety-Critical AI Applications: CNN-Based Traffic Sign Recognition Case Study. ISSRE Workshops 2019: 118-119 - [c6]Andrey Morozov, Kai Ding, Mikael Steurer, Klaus Janschek:
OpenErrorPro: A New Tool for Stochastic Model-Based Reliability and Resilience Analysis. ISSRE 2019: 303-312 - [c5]Kai Ding, Andrey Morozov, Klaus Janschek:
Efficient Model-Level Reliability Analysis of Simulink Models. SAFECOMP 2019: 139-154 - [i1]Clemens Dubslaff, Kai Ding, Andrey Morozov, Christel Baier, Klaus Janschek:
Breaking the Limits of Redundancy Systems Analysis. CoRR abs/1912.05364 (2019) - 2018
- [c4]Kai Ding, Andrey Morozov, Klaus Janschek:
Reliability Evaluation of Functionally Equivalent Simulink Implementations of a PID Controller under Silent Data Corruption. ISSRE 2018: 47-57 - [c3]Kai Ding, Andrey Morozov, Klaus Janschek:
MORE: MOdel-based REdundancy for Simulink. SAFECOMP 2018: 250-264 - 2017
- [c2]Kai Ding, Andrey Morozov, Klaus Janschek:
Classification of Hierarchical Fault-Tolerant Design Patterns. DASC/PiCom/DataCom/CyberSciTech 2017: 612-619 - [c1]Andrey Morozov, Kai Ding, Tao Chen, Klaus Janschek:
Test Suite Prioritization for Efficient Regression Testing of Model-Based Automotive Software. SATE 2017: 20-29
Coauthor Index
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