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Books and Theses
- 2023
[b1]Alexander Diedrich:
On Diagnosing Cyber-Physical Systems. Helmut Schmidt University, Hamburg, Germany, 2023
Journal Articles
- 2024
- [j2]Alexander Diedrich, Stefan Windmann, Oliver Niggemann:
Solving industrial fault diagnosis problems with quantum computers. Quantum Mach. Intell. 6(2): 66 (2024) - 2022
- [j1]Alexander Diedrich
, Oliver Niggemann:
On Residual-based Diagnosis of Physical Systems. Eng. Appl. Artif. Intell. 109: 104636 (2022)
Conference and Workshop Papers
- 2024
- [c14]René Heesch, Alessandro Cimatti, Jonas Ehrhardt, Alexander Diedrich, Oliver Niggemann:
A Lazy Approach to Neural Numerical Planning with Control Parameters. ECAI 2024: 4262-4270 - [c13]Jonas Ehrhardt, Phillip Johann Overlöper, Daniel Vranjes, Henrik S. Steude, Alexander Diedrich, Oliver Niggemann:
Using Modular Neural Networks for Anomaly Detection in Cyber-Physical Systems. ETFA 2024: 1-7 - [c12]Björn Ludwig, Alexander Diedrich, Oliver Niggemann:
Using Ontologies to Create Logical System Descriptions for Fault Diagnosis. ETFA 2024: 1-8 - [c11]Lukas Moddemann, Henrik Sebastian Steude, Alexander Diedrich, Ingo Pill, Oliver Niggemann:
Extracting Knowledge using Machine Learning for Anomaly Detection and Root-Cause Diagnosis. ETFA 2024: 1-8 - 2022
- [c10]Jonas Ehrhardt, Malte Ramonat, René Heesch, Kaja Balzereit, Alexander Diedrich, Oliver Niggemann:
An AI benchmark for Diagnosis, Reconfiguration & Planning. ETFA 2022: 1-8 - [c9]Kaja Balzereit, Alexander Diedrich, Daniel Kubus, Jonas Ginster, Andreas Bunte:
Generating Causal Hypotheses for Explaining Black-Box Industrial Processes. ICPS 2022: 1-6 - [c8]Alexander Diedrich, Patrick Deutschmann, Caroline Junker:
ServiceNavigator - A Bayesian Assistance System for Diagnosing Industrial Production Systems. ICPS 2022: 1-6 - 2021
- [c7]Oliver Niggemann, Alexander Diedrich, Christian Kühnert, Erik Pfannstiel, Joshua Schraven:
A Generic DigitalTwin Model for Artificial Intelligence Applications. ICPS 2021: 55-62 - [c6]Kaja Balzereit, Alexander Diedrich, Jonas Ginster, Stefan Windmann, Oliver Niggemann:
An Ensemble of Benchmarks for the Evaluation of AI Methods for Fault Handling in CPPS. INDIN 2021: 1-6 - 2019
- [c5]Alexander Diedrich, Alexander Maier, Oliver Niggemann:
Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory. AAAI 2019: 1452-1459 - 2018
- [c4]Alexander Diedrich, Oliver Niggemann:
Diagnosing Hybrid Cyber-Physical Systems using State-Space Models and Satisfiability Modulo Theory. DX 2018 - 2016
- [c3]Andreas Bunte, Alexander Diedrich, Oliver Niggemann:
Integrating semantics for diagnosis of manufacturing systems. ETFA 2016: 1-8 - [c2]Alexander Diedrich, Björn Böttcher, Oliver Niggemann:
Exposing Design Mistakes During Requirements Engineering by Solving Constraint Satisfaction Problems to Obtain Minimum Correction Subsets. ICAART (2) 2016: 280-287 - 2015
- [c1]Alexander Diedrich, Andreas Bunte, Alexander Maier, Oliver Niggemann:
Kognitive Architektur zum Konzeptlernen in technischen Systemen. ML4CPS 2015: 75-85
Informal and Other Publications
- 2024
- [i4]Alessandro Cimatti, Ingo Pill, Alexander Diedrich:
Fusing Causality, Reasoning, and Learning for Fault Management and Diagnosis (Dagstuhl Seminar 24031). Dagstuhl Reports 14(1): 25-48 (2024) - 2023
- [i3]Lukas Moddemann, Henrik Sebastian Steude, Alexander Diedrich, Oliver Niggemann:
Discret2Di - Deep Learning based Discretization for Model-based Diagnosis. CoRR abs/2311.03413 (2023) - [i2]Henrik S. Steude, Lukas Moddemann, Alexander Diedrich, Jonas Ehrhardt, Oliver Niggemann:
Diagnosis driven Anomaly Detection for CPS. CoRR abs/2311.15924 (2023) - 2020
- [i1]Oliver Niggemann, Alexander Diedrich, Christian Kühnert, Erik Pfannstiel, Joshua Schraven:
The DigitalTwin from an Artificial Intelligence Perspective. CoRR abs/2010.14376 (2020)
Coauthor Index
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