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DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains
Here we employ domain adaptation techniques$-$ Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)$-$ and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies.
DeepMerge: Classifying High-redshift Merging Galaxies with Deep Neural Networks
The test set classification accuracy of the CNN is $79\%$ for pristine and $76\%$ for noisy.
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