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Huber, Lilach Goren
31  Ergebnisse:
Personensuche X
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1

Physics-Informed Machine Learning for Predictive Maintenanc..:

, In: 2023 10th IEEE Swiss Conference on Data Science (SDS),
Huber, Lilach Goren ; Palme, Thomas ; Chao, Manuel Arias - p. 66-72 , 2023
Link: https://doi.org/10.1109/..
 
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2

Scaling Up Deep Learning Based Predictive Maintenance for C..:

, In: 2022 9th Swiss Conference on Data Science (SDS),
Ulmer, Markus ; Zgraggen, Jannik ; Pizza, Gianmarco. - p. 40-46 , 2022
Link: https://doi.org/10.1109/..
 
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3

Data Scarcity in Fault Detection for Solar Tracking Systems..:

Lüscher, Mila Francesca ; Zgraggen, Jannik ; Guo, Yuyan..
PHM Society European Conference.  8 (2024)  1 - p. 8 , 2024
Link: https://doi.org/10.36001..
 
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4

Uncertainty Informed Anomaly Scores with Deep Learning: Rob..:

Zgraggen, Jannik ; Pizza, Gianmarco ; Goren Huber, Lilach
PHM Society European Conference.  7 (2022)  1 - p. 530-540 , 2022
Link: https://doi.org/10.36001..
 
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5

Physics Informed Deep Learning for Tracker Fault Detection ..:

Zgraggen, Jannik ; Guo, Yuyan ; Notaristefano, Antonio.
Annual Conference of the PHM Society.  14 (2022)  1 - p. , 2022
Link: https://doi.org/10.36001..
 
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6

Transfer Learning Approaches for Wind Turbine Fault Detecti..:

Zgraggen, Jannik ; Ulmer, Markus ; Jarlskog, Eskil..
PHM Society European Conference.  6 (2021)  1 - p. 12 , 2021
Link: https://doi.org/10.36001..
 
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7

Big Data architecture for intelligent maintenance: a focus ..:

Lehmann, Claude ; Goren Huber, Lilach ; Horisberger, Thomas...
Journal of Big Data.  7 (2020)  1 - p. , 2020
Link: https://doi.org/10.1186/..
 
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8

Cross-Turbine Training of Convolutional Neural Networks for..:

Ulmer, Markus ; Jarlskog, Eskil ; Pizza, Gianmarco.
Annual Conference of the PHM Society.  12 (2020)  1 - p. 10 , 2020
Link: https://doi.org/10.36001..
 
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9

A Generic Machine Learning Framework for Fully-Unsupervised..:

Ulmer, Markus ; Zgraggen, Jannik ; Huber, Lilach Goren
http://arxiv.org/abs/2308.13352.  , 2023
Link: http://arxiv.org/abs/230..
 
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10

Physics-informed machine learning for predictive maintenanc..:

Goren Huber, Lilach ; Palmé, Thomas ; Arias Chao, Manuel
https://doi.org/10.1109/SDS57534.2023.00016.  , 2023
Link: https://hdl.handle.net/1..
 
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11

Hybride Instandhaltung : wie fliesst das Fachwissen in die ..:

Goren Huber, Lilach ; Palmé, Jan Thomas ; Arias Chao, Manuel
https://doi.org/10.21256/zhaw-29515.  , 2023
Link: https://hdl.handle.net/1..
 
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12

Uncertainty informed anomaly scores with deep learning : ro..:

Zgraggen, Jannik ; Pizza, Gianmarco ; Goren Huber, Lilach
https://doi.org/10.36001/phme.2022.v7i1.3342.  , 2022
Link: https://hdl.handle.net/1..
 
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13

Predictive Maintenance mit Physics-Informed-Deep-Learning :..:

Goren Huber, Lilach ; Notaristefano, Antonio
https://doi.org/10.21256/zhaw-25292.  , 2022
Link: https://hdl.handle.net/1..
 
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14

Physics informed deep learning for tracker fault detection ..:

Zgraggen, Jannik ; Guo, Yuyan ; Notaristefano, Antonio.
https://doi.org/10.36001/phmconf.2022.v14i1.3235.  , 2022
Link: https://hdl.handle.net/1..
 
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15

Transfer learning approaches for wind turbine fault detecti..:

Zgraggen, Jannik ; Ulmer, Markus ; Jarlskog, Eskil..
https://doi.org/10.21256/zhaw-22774.  , 2021
Link: https://doi.org/10.21256..
 
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