Olga Fink

Orcid: 0000-0002-9546-1488

According to our database1, Olga Fink authored at least 105 papers between 2013 and 2024.

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

Timeline

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Bibliography

2024
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT Systems.
IEEE Internet Things J., July, 2024

Incentive Mechanism in the Sponsored Content Market With Network Effects.
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

Deep Koopman Operator-based degradation modelling.
Reliab. Eng. Syst. Saf., 2024

Algorithm-Informed Graph Neural Networks for Leakage Detection and Localization in Water Distribution Networks.
CoRR, 2024

Learning Physics-Consistent Material Behavior Without Prior Knowledge.
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

IM-Context: In-Context Learning for Imbalanced Regression Tasks.
CoRR, 2024

Interpretable Prognostics with Concept Bottleneck Models.
CoRR, 2024

MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities.
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

ThermoNeRF: Multimodal Neural Radiance Fields for Thermal Novel View Synthesis.
CoRR, 2024

Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making.
CoRR, 2024

Uncertainty-Guided Alignment for Unsupervised Domain Adaptation in Regression.
CoRR, 2024

Robust time series denoising with learnable wavelet packet transform.
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

Multi-agent actor-critic with time dynamical opponent model.
Neurocomputing, 2023

Semi-Supervised Health Index Monitoring with Feature Generation and Fusion.
CoRR, 2023

Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis.
CoRR, 2023

NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation.
CoRR, 2023

From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring.
CoRR, 2023

Graph Neural Networks for Dynamic Modeling of Roller Bearing.
CoRR, 2023

A Comparison of Residual-based Methods on Fault Detection.
CoRR, 2023

Dynamic Graph Attention for Anomaly Detection in Heterogeneous Sensor Networks.
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

Gemtelligence: Accelerating Gemstone classification with Deep Learning.
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

Incentive Mechanism in the Sponsored Content Market with Network Effect.
CoRR, 2023

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization.
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

A prescriptive Dirichlet power allocation policy with deep reinforcement learning.
Reliab. Eng. Syst. Saf., 2022

Maintenance scheduling of manufacturing systems based on optimal price of the network.
Reliab. Eng. Syst. Saf., 2022

Fusing physics-based and deep learning models for prognostics.
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

Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction.
CoRR, 2022

Controlled Generation of Unseen Faults for Partial and OpenSet&Partial Domain Adaptation.
CoRR, 2022

Learning Physics-Consistent Particle Interactions.
CoRR, 2022

Artificial intelligence across company borders.
Commun. ACM, 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

Learnable Wavelet Packet Transform for Data-Adapted Spectrograms.
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

Continual Test-Time Domain Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Missing-Class-Robust Domain Adaptation by Unilateral Alignment.
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

Interpretable Detection of Partial Discharge in Power Lines with Deep Learning.
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

Canonical Polyadic Decomposition and Deep Learning for Machine Fault Detection.
CoRR, 2021

Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series.
CoRR, 2021

Uncertainty-aware Remaining Useful Life predictor.
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

Uncertainty-Aware Prognosis via Deep Gaussian Process.
IEEE Access, 2021

Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation.
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

Battery Model Calibration with Deep Reinforcement Learning.
CoRR, 2020

Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition.
CoRR, 2020

Transferring Complementary Operating Conditions for Anomaly Detection.
CoRR, 2020

Interpretable Partial Discharge Detection with Temporal Convolution and Pulse Activation Maps: An application to Power Lines.
CoRR, 2020

Real-Time Model Calibration with Deep Reinforcement Learning.
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

Missing-Class-Robust Domain Adaptation by Unilateral Alignment for Fault Diagnosis.
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

Domain Adaptive Transfer Learning for Fault Diagnosis.
CoRR, 2019

Unsupervised Fault Detection in Varying Operating Conditions.
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
Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.
IEEE Trans. Neural Networks Learn. Syst., 2016

Online sequential extreme learning machines for fault detection.
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

Quantifying the reliability of fault classifiers.
Inf. Sci., 2014

2013
Predicting time series of railway speed restrictions with time-dependent machine learning techniques.
Expert Syst. Appl., 2013


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