3 citations · 3 across the 2 of their papers we have counts for
3 papers
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…
astro-ph.GA2021★ 3 cited
Robustness of deep learning algorithms in astronomy -- galaxy morphology studies
A. Ćiprijanović, D. Kafkes, G. N. Perdue +6
Deep learning models are being increasingly adopted in wide array of scientific domains, especially to handle high-dimensionality and volume of the scientific data. However, these…
astro-ph.IM2019
Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan"
J. Amundson, J. Annis, C. Avestruz +27
We present a response to the 2018 Request for Information (RFI) from the NITRD, NCO, NSF regarding the "Update to the 2016 National Artificial Intelligence Research and Development…