2 citations · 5 across the 4 of their papers we have counts for
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astro-ph.GA2023★ 2 cited
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
A. Ćiprijanović, A. Lewis, K. Pedro +4
Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to t…
astro-ph.GA2022★ 2 cited
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
Aleksandra Ćiprijanović, Ashia Lewis, Kevin Pedro +4
In the era of big astronomical surveys, our ability to leverage artificial intelligence algorithms simultaneously for multiple datasets will open new avenues for scientific discove…