Adapting Data-Driven Techniques to Improve Surrogate Machine Learning Model Performance
We demonstrate the adaption of three established methods to the field of surrogate machine learning model development. These methods are data augmentation, custom loss functions and fine-tuning of pre-trained models. Each of these methods have seen widespread use in the field of machine learning, ho...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10061162/ |