1 code implementation • 2 Mar 2021 • A. Ćiprijanović, D. Kafkes, K. Downey, S. Jenkins, G. N. Perdue, S. Madireddy, T. Johnston, G. F. Snyder, B. Nord
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.
no code implementations • 6 Nov 2020 • A. Ćiprijanović, D. Kafkes, S. Jenkins, K. Downey, G. N. Perdue, S. Madireddy, T. Johnston, B. Nord
In astronomy, neural networks are often trained on simulated data with the prospect of being applied to real observations.