"Know Thyself" - Computational Self-Reflection in Intelligent Technical Systems. - Sven Tomforde; Jörg Hähner; Sebastian von Mammen; Christian Gruhl; Bernhard Sick; Kurt Geihs (SASO Workshops, 2014)

A building block for awareness in technical systems: Online novelty detection and reaction with an application in intrusion detection. - Christian Gruhl; Bernhard Sick; Arno Wacker; Sven Tomforde; Jörg Hähner (iCAST, 2015)

Towards Autonomous Self-Tests at Runtime. - Henner Heck; Stefan Rudolph; Christian Gruhl; Arno Wacker; Jörg Hähner; Bernhard Sick; Sven Tomforde (FAS*W@SASO/ICCAC, 2016)

Detecting Novel Processes with CANDIES - An Holistic Novelty Detection Technique based on Probabilistic Models. - Christian Gruhl; Bernhard Sick (CoRR, 2016)

Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions. - Christian Gruhl; Bernhard Sick (CoRR, 2016)

Towards automation of knowledge understanding: An approach for probabilistic generative classifiers. - Dominik Fisch; Christian Gruhl; Edgar Kalkowski; Bernhard Sick; Seppo J. Ovaska (Inf. Sci., 2016)

Self-Improving System Integration - Status and Challenges after Five Years of SISSY. - Kirstie L. Bellman; Jean Botev; Ada Diaconescu; Lukas Esterle; Christian Gruhl; Christopher Landauer; Peter R. Lewis 001; Anthony Stein; Sven Tomforde; Rolf P. Würtz (FAS*W@SASO/ICAC, 2018)

Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. - Christian Gruhl; Sven Tomforde; Bernhard Sick (FAS*W@SASO/ICAC, 2018)

Novelty detection with CANDIES: a holistic technique based on probabilistic models. - Christian Gruhl; Bernhard Sick (Int. J. Mach. Learn. Cybern., 2018)

CHARIOT - Towards a Continuous High-Level Adaptive Runtime Integration Testbed. - Chloe M. Barnes; Kirstie L. Bellman; Jean Botev; Ada Diaconescu; Lukas Esterle; Christian Gruhl; Christopher Landauer; Peter R. Lewis 001; Phyllis R. Nelson; Anthony Stein; Christopher Stewart; Sven Tomforde (FAS*W@SASO/ICAC, 2019)

Self-Improving System Integration - On a Definition and Characteristics of the Challenge. - Kirstie L. Bellman; Christian Gruhl; Christopher Landauer; Sven Tomforde (FAS*W@SASO/ICAC, 2019)

Normal-Wishart Clustering for Novelty Detection. - Christian Gruhl; Jörn Schmeißing; Sven Tomforde; Bernhard Sick (ACSOS Companion, 2020)

Fairness, Performance, and Robustness: Is There a CAP Theorem for Self-adaptive and Self-organising Systems? - Sven Tomforde; Christian Gruhl (ACSOS Companion, 2020)

A Swarm-fleet Infrastructure as a Scenario for Proactive, Hybrid Adaptation of System Behaviour. - Sven Tomforde; Christian Gruhl; Bernhard Sick (ACSOS Companion, 2020)

Novelty Based Driver Identification on RR Intervals from ECG Data. - Florian Heidecker; Christian Gruhl; Bernhard Sick (ICPR Workshops (4), 2020)

Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. - Tuan Pham Minh; Daniel Kottke; Anna Tsarenko; Christian Gruhl; Bernhard Sick (IJCNN, 2020)

Digital Shadows in Self-Improving System Integration: A Concept U sing Generative Modelling. - Ghassan Al-Falouji; Christian Gruhl; Sven Tomforde (ACSOS-C, 2021)

The Problem with Real-World Novelty Detection - Issues in Multivariate Probabilistic Models. - Christian Gruhl; Abdul Hannan; Zhixin Huang; Chandana Nivarthi; Stephan Vogt (ACSOS-C, 2021)

OHODIN - Online Anomaly Detection for Data Streams. - Christian Gruhl; Sven Tomforde (ACSOS-C, 2021)

Anomaly based Resilient Network Intrusion Detection using Inferential Autoencoders. - Abdul Hannan; Christian Gruhl; Bernhard Sick (CSR, 2021)

Towards Organic Distribution Systems - The Vision of Self-Configuring, Self-Organising, Self-Healing, and Self-Optimising Power Distribution Management. - Inga Löser; Martin Braun 002; Christian Gruhl; Jan-Hendrik Menke; Bernhard Sick; Sven Tomforde (CoRR, 2021)

Self-improving system integration: Mastering continuous change. - Kirstie L. Bellman; Jean Botev; Ada Diaconescu; Lukas Esterle; Christian Gruhl; Christopher Landauer; Peter R. Lewis 001; Phyllis R. Nelson; Evangelos Pournaras; Anthony Stein; Sven Tomforde (Future Gener. Comput. Syst., 2021)

Novelty detection in continuously changing environments. - Christian Gruhl; Bernhard Sick; Sven Tomforde (Future Gener. Comput. Syst., 2021)

A Heuristic for an Online Applicability of Anomaly Detection Techniques. - Ghassan Al-Falouji; Christian Gruhl; Torben Neumann; Sven Tomforde (ACSOS-C, 2022)

Self-Aware Microsystems. - Christian Gruhl; Sven Tomforde; Bernhard Sick (ACSOS-C, 2022)

NDNET: A Unified Framework for Anomaly and Novelty Detection. - Jens Decke; Jörn Schmeißing; Diego Botache; Maarten Bieshaar; Bernhard Sick; Christian Gruhl (ARCS, 2022)

Proactive hybrid learning and optimisation in self-adaptive systems: The swarm-fleet infrastructure scenario. - Christian Krupitzer; Christian Gruhl; Bernhard Sick; Sven Tomforde (Inf. Softw. Technol., 2022)

Social Machines. - Claude Draude; Christian Gruhl; Gerrit Hornung; Jonathan Kropf; Jörn Lamla; Jan Marco Leimeister; Bernhard Sick; Gerd Stumme (Inform. Spektrum, 2022)

Novelty detection for multivariate data streams with probabilistic models. - Christian Gruhl (2022)

Self- Integration and Agent Compatibility. - Christian Gruhl; Bernhard Sick (ACSOS-C, 2023)

Self-awareness in Cyber-Physical Systems: Recent Developments and Open Challenges. - Lukas Esterle; Nikil D. Dutt; Christian Gruhl; Peter R. Lewis 001; Lucio Marcenaro; Carlo S. Regazzoni; Axel Jantsch (DATE, 2023)

DADO - Low-Cost Query Strategies for Deep Active Design Optimization. - Jens Decke; Christian Gruhl; Lukas Rauch; Bernhard Sick (ICMLA, 2023)

DADO - Low-Cost Selection Strategies for Deep Active Design Optimization. - Jens Decke; Christian Gruhl; Lukas Rauch; Bernhard Sick (CoRR, 2023)

Self-Aware Control for Autonomous Underwater Vehicles. - Jens Decke; Florian Gerland; Thomas Schomberg; Olaf Wünsch; Bernhard Sick; Christian Gruhl (ACSOS-C, 2024)

An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing. - Jens Decke; Arne Jenß; Bernhard Sick; Christian Gruhl (ARCS, 2024)

From Structured to Unstructured: A Comparative Analysis of Computer Vision and Graph Models in Solving Mesh-Based PDEs. - Jens Decke; Olaf Wünsch; Bernhard Sick; Christian Gruhl (ARCS, 2024)

Active Learning with Physics-Informed Graph Neural Networks on Unstructured Meshes. - Jens Decke; Alexander Heinen; Bernhard Sick; Christian Gruhl (IAL@PKDD/ECML, 2024)

Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Chandana Priya Nivarthi; Bernhard Sick; Christian Gruhl (ICPR (27), 2024)

Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction. - Zhixin Huang; Yujiang He; Chandana Priya Nivarthi; Christian Gruhl; Bernhard Sick (IJCNN, 2024)

Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection. - Chandana Priya Nivarthi; Zhixin Huang; Christian Gruhl; Bernhard Sick (IJCNN, 2024)

Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems. - Martin Braun 002; Christian Gruhl; Christian A. Hans; Philipp Härtel; Christoph Scholz 001; Bernhard Sick; Malte Siefert; Florian Steinke; Olaf Stursberg; Sebastian Wende-von Berg (ISGT EUROPE, 2024)