Olga Fink
Orcid: 0000-0002-9546-1488
According to our database1,
Olga Fink
authored at least 105 papers
between 2013 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT Systems.
IEEE Internet Things J., July, 2024
IEEE Trans. Comput. Soc. Syst., February, 2024
Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction.
Reliab. Eng. Syst. Saf., February, 2024
Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis.
IEEE Trans. Cybern., January, 2024
Algorithm-Informed Graph Neural Networks for Leakage Detection and Localization in Water Distribution Networks.
CoRR, 2024
Graph Neural Networks for Virtual Sensing in Complex Systems: Addressing Heterogeneous Temporal Dynamics.
CoRR, 2024
Simplifying Source-Free Domain Adaptation for Object Detection: Effective Self-Training Strategies and Performance Insights.
CoRR, 2024
Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision.
CoRR, 2024
Cut-and-Paste with Precision: a Content and Perspective-aware Data Augmentation for Road Damage Detection.
CoRR, 2024
Continuous Test-time Domain Adaptation for Efficient Fault Detection under Evolving Operating Conditions.
CoRR, 2024
CUT: A Controllable, Universal, and Training-Free Visual Anomaly Generation Framework.
CoRR, 2024
Prescribing Optimal Health-Aware Operation for Urban Air Mobility with Deep Reinforcement Learning.
CoRR, 2024
Physics-Enhanced Graph Neural Networks For Soft Sensing in Industrial Internet of Things.
CoRR, 2024
Graph Neural Networks for Electric and Hydraulic Data Fusion to Enhance Short-term Forecasting of Pumped-storage Hydroelectricity.
CoRR, 2024
Virtual Sensor for Real-Time Bearing Load Prediction Using Heterogeneous Temporal Graph Neural Networks.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Adv. Eng. Informatics, 2024
2023
Smart filter aided domain adversarial neural network for fault diagnosis in noisy industrial scenarios.
Eng. Appl. Artif. Intell., November, 2023
Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity markets.
Expert Syst. Appl., September, 2023
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units.
Reliab. Eng. Syst. Saf., April, 2023
Controlled generation of unseen faults for <i>Partial</i> and <i>Open-Partial</i> domain adaptation.
Reliab. Eng. Syst. Saf., 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring.
CoRR, 2023
CoRR, 2023
Smart filter aided domain adversarial neural network: An unsupervised domain adaptation method for fault diagnosis in noisy industrial scenarios.
CoRR, 2023
Non-contact Sensing for Anomaly Detection in Wind Turbine Blades: A focus-SVDD with Complex-Valued Auto-Encoder Approach.
CoRR, 2023
Domain knowledge-informed Synthetic fault sample generation with Health Data Map for cross-domain Planetary Gearbox Fault Diagnosis.
CoRR, 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial.
CoRR, 2023
Collective Relational Inference for learning physics-consistent heterogeneous particle interactions.
CoRR, 2023
Federated Learning with Uncertainty-Based Client Clustering for Fleet-Wide Fault Diagnosis.
CoRR, 2023
Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Spatial-Temporal Graph Attention Fuser for Calibration in IoT Air Pollution Monitoring Systems.
Proceedings of the 2023 IEEE SENSORS, Vienna, Austria, October 29 - Nov. 1, 2023, 2023
DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Integrating Expert Knowledge With Domain Adaptation for Unsupervised Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2022
Reliab. Eng. Syst. Saf., 2022
Maintenance scheduling of manufacturing systems based on optimal price of the network.
Reliab. Eng. Syst. Saf., 2022
Reliab. Eng. Syst. Saf., 2022
A Comprehensive Review of Digital Twin - Part 1: Modeling and Twinning Enabling Technologies.
CoRR, 2022
Contrastive Feature Learning for Fault Detection and Diagnostics in Railway Applications.
CoRR, 2022
A Comprehensive Review of Digital Twin - Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives.
CoRR, 2022
Multi-Agent Reinforcement Learning with Graph Convolutional Neural Networks for optimal Bidding Strategies of Generation Units in Electricity Markets.
CoRR, 2022
CoRR, 2022
Controlled Generation of Unseen Faults for Partial and OpenSet&Partial Domain Adaptation.
CoRR, 2022
Vacuum Circuit Breaker Closing Time Key Moments Detection via Vibration Monitoring: A Run-to-Failure Study.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
DG-Mix: Domain Generalization for Anomalous Sound Detection Based on Self-Supervised Learning.
Proceedings of the 7th Workshop on Detection and Classification of Acoustic Scenes and Events 2022, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
IEEE Trans. Ind. Electron., 2021
Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types.
Sensors, 2021
Sensors, 2021
Multi-agent maintenance scheduling based on the coordination between central operator and decentralized producers in an electricity market.
Reliab. Eng. Syst. Saf., 2021
Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer.
Knowl. Based Syst., 2021
Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders.
Neurocomputing, 2021
Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics.
Data, 2021
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units.
CoRR, 2021
CoRR, 2021
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series.
CoRR, 2021
Decision Support System for an Intelligent Operator of Utility Tunnel Boring Machines.
CoRR, 2021
Hierarchical multi-agent predictive maintenance scheduling for trains using price-based approach.
Comput. Ind. Eng., 2021
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
2020
Potential, challenges and future directions for deep learning in prognostics and health management applications.
Eng. Appl. Artif. Intell., 2020
Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition.
CoRR, 2020
Interpretable Partial Discharge Detection with Temporal Convolution and Pulse Activation Maps: An application to Power Lines.
CoRR, 2020
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks.
CoRR, 2020
Time Series to Images: Monitoring the Condition of Industrial Assets with Deep Learning Image Processing Algorithms.
CoRR, 2020
CoRR, 2020
Improving generalization of deep fault detection models in the presence of mislabeled data.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020
Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search.
Proceedings of the Computer Vision - ECCV 2020, 2020
2019
Knowledge-Induced Learning with Adaptive Sampling Variational Autoencoders for Open Set Fault Diagnostics.
CoRR, 2019
Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models.
CoRR, 2019
Fully Unsupervised Feature Alignment for Critical System Health Monitoring with Varied Operating Conditions.
CoRR, 2019
Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019
2018
Combined Fault Location and Classification for Power Transmission Lines Fault Diagnosis With Integrated Feature Extraction.
IEEE Trans. Ind. Electron., 2018
Feature Learning for Fault Detection in High-Dimensional Condition-Monitoring Signals.
CoRR, 2018
2017
Fault detection based on signal reconstruction with Auto-Associative Extreme Learning Machines.
Eng. Appl. Artif. Intell., 2017
2016
IEEE Trans. Neural Networks Learn. Syst., 2016
Proceedings of the IEEE International Conference on Prognostics and Health Management, 2016
2015
A Classification Framework for Predicting Components' Remaining Useful Life Based on Discrete-Event Diagnostic Data.
IEEE Trans. Reliab., 2015
Fuzzy Classification With Restricted Boltzman Machines and Echo-State Networks for Predicting Potential Railway Door System Failures.
IEEE Trans. Reliab., 2015
2014
Predicting component reliability and level of degradation with complex-valued neural networks.
Reliab. Eng. Syst. Saf., 2014
2013
Predicting time series of railway speed restrictions with time-dependent machine learning techniques.
Expert Syst. Appl., 2013