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2020 – today
- 2022
[b1]Ryan Hausen:
Large Scale Analysis of Astronomical Data Using Machine Learning and Visualization Techniques. University of California, Santa Cruz, USA, 2022- [j1]Ryan Hausen
, Brant Robertson:
FitsMap: A simple, lightweight tool for displaying interactive astronomical image and catalog data. Astron. Comput. 39: 100586 (2022) - [i2]Ryan Hausen, Brant Robertson:
Partial-Attribution Instance Segmentation for Astronomical Source Detection and Deblending. CoRR abs/2201.04714 (2022) - 2020
- [c3]Todd W. Neller, Stephen Keeley, Michael Guerzhoy, Wolfgang Hönig, Jiaoyang Li, Sven Koenig, Ameet Soni, Krista Thomason, Lisa Zhang, Bibin Sebastian, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, James Allingham, Sejong Yoon, Jonathan Chen, Tom Larsen, Marion Neumann, Narges Norouzi, Ryan Hausen, Matthew Evett:
Model AI Assignments 2020. AAAI 2020: 13509-13511
2010 – 2019
- 2019
- [i1]Ryan Hausen, Brant Robertson:
Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data. CoRR abs/1906.11248 (2019) - 2018
- [c2]Narges Norouzi, Ryan Hausen:
Quantitative Evaluation of Student Engagement in a Large-Scale Introduction to Programming Course using a Cloud-based Automatic Grading System. FIE 2018: 1-5 - 2014
- [c1]Ryan Hausen, Bin Tang, Samuel Sambasivan, Simon Lin:
Maximizing Data Preservation Time in Linear Sensor Networks. MASS 2014: 513-514
Coauthor Index
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