Alexander Diedrich

Orcid: 0000-0002-8674-6895

According to our database1, Alexander Diedrich authored at least 25 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Solving industrial fault diagnosis problems with quantum computers.
Quantum Mach. Intell., December, 2024

Fusing Causality, Reasoning, and Learning for Fault Management and Diagnosis (Dagstuhl Seminar 24031).
Dagstuhl Reports, 2024

AAAI Workshop on AI Planning for Cyber-Physical Systems - CAIPI24.
CoRR, 2024

Extracting Knowledge using Machine Learning for Anomaly Detection and Root-Cause Diagnosis.
Proceedings of the 29th IEEE International Conference on Emerging Technologies and Factory Automation, 2024

Using Ontologies to Create Logical System Descriptions for Fault Diagnosis.
Proceedings of the 29th IEEE International Conference on Emerging Technologies and Factory Automation, 2024

Using Modular Neural Networks for Anomaly Detection in Cyber-Physical Systems.
Proceedings of the 29th IEEE International Conference on Emerging Technologies and Factory Automation, 2024

A Lazy Approach to Neural Numerical Planning with Control Parameters.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Using Multi-Modal LLMs to Create Models for Fault Diagnosis (Short Paper).
Proceedings of the 35th International Conference on Principles of Diagnosis and Resilient Systems, 2024

Summary of "A Lazy Approach to Neural Numerical Planning with Control Parameters" (Extended Abstract).
Proceedings of the 35th International Conference on Principles of Diagnosis and Resilient Systems, 2024

Inferring Sensor Placement Using Critical Pairs and Satisfiability Modulo Theory.
Proceedings of the 35th International Conference on Principles of Diagnosis and Resilient Systems, 2024

2023
On Diagnosing Cyber-Physical Systems.
PhD thesis, 2023

Diagnosis driven Anomaly Detection for CPS.
CoRR, 2023

Discret2Di - Deep Learning based Discretization for Model-based Diagnosis.
CoRR, 2023

2022
On Residual-based Diagnosis of Physical Systems.
Eng. Appl. Artif. Intell., 2022

ServiceNavigator - A Bayesian Assistance System for Diagnosing Industrial Production Systems.
Proceedings of the 5th IEEE International Conference on Industrial Cyber-Physical Systems, 2022

Generating Causal Hypotheses for Explaining Black-Box Industrial Processes.
Proceedings of the 5th IEEE International Conference on Industrial Cyber-Physical Systems, 2022

An AI benchmark for Diagnosis, Reconfiguration & Planning.
Proceedings of the 27th IEEE International Conference on Emerging Technologies and Factory Automation, 2022

2021
An Ensemble of Benchmarks for the Evaluation of AI Methods for Fault Handling in CPPS.
Proceedings of the 19th IEEE International Conference on Industrial Informatics, 2021

A Generic DigitalTwin Model for Artificial Intelligence Applications.
Proceedings of the 4th IEEE International Conference on Industrial Cyber-Physical Systems, 2021

2020
The DigitalTwin from an Artificial Intelligence Perspective.
CoRR, 2020

2019
Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Diagnosing Hybrid Cyber-Physical Systems using State-Space Models and Satisfiability Modulo Theory.
Proceedings of the 29th International Workshop on Principles of Diagnosis co-located with 10th IFAC Symposium on Fault Detection, 2018

2016
Exposing Design Mistakes During Requirements Engineering by Solving Constraint Satisfaction Problems to Obtain Minimum Correction Subsets.
Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART 2016), 2016

Integrating semantics for diagnosis of manufacturing systems.
Proceedings of the 21st IEEE International Conference on Emerging Technologies and Factory Automation, 2016

2015
Kognitive Architektur zum Konzeptlernen in technischen Systemen.
Proceedings of the Machine Learning for Cyber Physical Systems, 2015


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