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Sensors (Basel, Switzerland)
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December 17, 2024
Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis
Florent Forest, Olga Fink
Nature Communications
|
January 15, 2026
A physics-informed graph neural network conserving linear and angular momentum for dynamical systems
Vinay Sharma, Olga Fink
Nature Communications
|
July 27, 2025
Integrating physics and topology in neural networks for learning rigid body dynamics
Amaury Wei, Olga Fink
IEEE Transactions on Neural Networks and Learning Systems
|
April 25, 2015
Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction
Ronay Ak, Olga Fink, Enrico Zio
Proceedings of the National Academy of Sciences of the United States of America
|
February 19, 2022
Fully learnable deep wavelet transform for unsupervised monitoring of high-frequency time series
Gabriel Michau, Gaetan Frusque, Olga Fink
Sensors (Basel, Switzerland)
|
June 2, 2021
Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types
Katharina Rombach, Gabriel Michau, Olga Fink
PNAS Nexus
|
January 30, 2023
Learning physics-consistent particle interactions
Zhichao Han, David S Kammer, Olga Fink
Sensors (Basel, Switzerland)
|
April 3, 2021
Interpretable Detection of Partial Discharge in Power Lines with Deep Learning
Gabriel Michau, Chi-Ching Hsu, Olga Fink
Nature Communications
|
April 12, 2024
Collective relational inference for learning heterogeneous interactions
Zhichao Han, Olga Fink, David S Kammer
IEEE Transactions on Neural Networks and Learning Systems
|
March 3, 2025
NNG-Mix: Improving Semi-Supervised Anomaly Detection With Pseudo-Anomaly Generation
Hao Dong, Gaetan Frusque, Yue Zhao, et al.
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Search research articles
Search
Showing results (1-10 of 14) with videos related to
Sort By:
Page
of 2
Sensors (Basel, Switzerland)
|
December 17, 2024
Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis
Florent Forest, Olga Fink
Nature Communications
|
January 15, 2026
A physics-informed graph neural network conserving linear and angular momentum for dynamical systems
Vinay Sharma, Olga Fink
Nature Communications
|
July 27, 2025
Integrating physics and topology in neural networks for learning rigid body dynamics
Amaury Wei, Olga Fink
IEEE Transactions on Neural Networks and Learning Systems
|
April 25, 2015
Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction
Ronay Ak, Olga Fink, Enrico Zio
Proceedings of the National Academy of Sciences of the United States of America
|
February 19, 2022
Fully learnable deep wavelet transform for unsupervised monitoring of high-frequency time series
Gabriel Michau, Gaetan Frusque, Olga Fink
Sensors (Basel, Switzerland)
|
June 2, 2021
Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types
Katharina Rombach, Gabriel Michau, Olga Fink
PNAS Nexus
|
January 30, 2023
Learning physics-consistent particle interactions
Zhichao Han, David S Kammer, Olga Fink
Sensors (Basel, Switzerland)
|
April 3, 2021
Interpretable Detection of Partial Discharge in Power Lines with Deep Learning
Gabriel Michau, Chi-Ching Hsu, Olga Fink
Nature Communications
|
April 12, 2024
Collective relational inference for learning heterogeneous interactions
Zhichao Han, Olga Fink, David S Kammer
IEEE Transactions on Neural Networks and Learning Systems
|
March 3, 2025
NNG-Mix: Improving Semi-Supervised Anomaly Detection With Pseudo-Anomaly Generation
Hao Dong, Gaetan Frusque, Yue Zhao, et al.
Page
of 2